Python Developer Jobs in Egypt

<p>We are looking for a QA / ML Tester – Evaluation Framework to ensure the quality, reliability, and correctness of evaluation systems used across enterprise AI and agent-based platforms. In this role, you will design and execute validation strategies for evaluation frameworks, test evaluator behavior across multiple scenarios, and verify the accuracy of automated quality assessment pipelines. You will work closely with AI engineers, platform teams, and quality specialists to establish confidence in evaluation results and support enterprise-grade AI governance.</p><p><b><br></b></p><p><b>What project we have for you</b></p><p>Our customer is a multinational corporation with more than a century of history and offices in over 180 countries. Their most ambitious goal at the time is to introduce a range of Reduced-Risk Products (RRPs). The target audience is more than 1 billion consumers around the globe. IT platform hosts 700+ applications.</p><p>Intellia’s mission is to help the client with the engineering of a comprehensive software ecosystem for a game-changing IoT product on the margin of innovative consumer experience and cutting-edge technology. Our teams are involved in the engineering of core platform components for best-in-class eCommerce, Digital Marketing and IoT solutions. As an Engineer, you will become a part of Core Architecture Team and be responsible for the architecture, implementation of best practices in our Digital Engineering Enterprise Platform.</p><p>The Platform is a set of services and internet applications that accelerate the development and delivery of software applications by taking care of common SDLC challenges. The Platform provides access and consumption for engineering teams to a set of services, technologies, practices for their development and for operating their application, ensuring a set of compliance and best practices.</p><p><br></p><p>What you will do</p><p>Design, implement, and maintain automated test suites for AI evaluation frameworks and evaluation pipelines.</p><p>Develop Python-based test automation using pytest to validate evaluator behavior, quality scoring, and framework reliability.</p><p>Create and maintain known-good and known-bad test datasets, sessions, and workflows for evaluator correctness validation.</p><p>Validate the accuracy and consistency of evaluation results across different agent workflows, prompts, tools, and execution scenarios.</p><p>Design and execute integration tests for on-demand evaluation workflows integrated into CI/CD pipelines.</p><p>Verify online evaluation behavior, sampling accuracy, and evaluation result consistency in production-like environments.</p><p>Conduct functional testing of evaluation components, including evaluator execution flows, scoring logic, and result aggregation.</p><p>Collaborate with AI and platform engineering teams to identify edge cases, failure scenarios, and evaluation blind spots.</p><p>Validate workflow compliance, tool execution assessment, and end-to-end quality evaluation processes.</p><p>Support feasibility assessments for applying evaluation frameworks to non-AgentCore runtimes and alternative AI execution environments.</p><p>Analyze defects, inconsistencies, and quality regressions within evaluation systems and provide actionable recommendations.</p><p>Contribute to quality assurance standards, testing methodologies, and best practices for AI evaluation platforms.</p><p>What you need for this</p><p>Skills:</p><p><br></p><p>• Python test automation (pytest)</p><p>• Evaluator correctness testing (known-good / known-bad session pairs)</p><p>• On-demand mode integration testing with CI/CD</p><p>• Online mode sampling accuracy validation</p><p>• Non-AgentCore runtime feasibility assessment methodology&nbsp;</p><p><br></p><p>Experience:</p><p><br></p><p>• 4+ years QA or ML testing engineering</p><p>• AI/LLM system quality testing</p><p>• Integration test design for evaluation pipelines&nbsp;</p><p>• Experience with AWS environment&nbsp;</p><p><br></p><p>Nice-to-have</p><p><br></p><p>• AWS AgentCore Evaluation API testing</p><p>• OpenTelemetry trace-based evaluation input testing</p><p>• Multi-evaluator execution correctness testing</p><p><strong>Desired Candidate Profile</strong></p><p><br></p>

We are looking for a skilled AI Data Engineer to join our team and play a key role in building and maintaining scalable data platforms and AI-ready pipelines within banking and payments systems.<br><br>⚙️ Key Responsibilities Build and maintain data pipelines (batch, micro-batch, real-time) for banking and payments data Develop AI-ready datasets for ML use cases (fraud detection, credit scoring, AML/KYC) Implement data ingestion frameworks from multiple sources (core banking, APIs, payment gateways) Design and manage data storage solutions (Data Lake / Lakehouse / SQL & NoSQL) Ensure data quality, consistency, and validation across workflows Support feature engineering and ML pipelines Implement streaming solutions (Kafka / Event Hub) for real-time processing Optimize performance for handling large-scale transactional datasets Ensure compliance with data security and regulations (PCI DSS, GDPR) Contribute to CI/CD pipelines and Dev Ops practices<br>????️ Required Skills✅ Core:Strong experience in Python & SQLHands-on experience with Spark / Databricks✅ Data Engineering Tools:Azure Data Factory (ADF) Airflow / DBT / SSIS✅ Streaming:Kafka / Event Hub✅ Cloud:Azure (preferred) AWS / GCP✅ Knowledge:Data modeling (OLTP / OLAP) AI/ML data preparation pipelines Handling structured & unstructured data<br>???? Domain Expertise (Must Have) Experience in Banking / Fintech / Financial Services Strong understanding of:Payment flows Transaction processing ISO 20022 / SWIFT / Card systems Exposure to:Fraud Detection AML / KYC datasets<br>???? Qualifications Bachelor’s in Computer Science / Data Engineering or related field3–5 years of experience in Data Engineering Banking experience is highly preferred<br>⭐ Nice to Have Delta Lake / Lakehouse architecture Real-time analytics / event-driven systems Docker / Kubernetes / Dev Ops Data governance tools

???? Senior Data Science Consultant – Cards Marketing Analytics???? Location: Egypt (Onsite – Client Office)???? Term: 12 months???? Eligibility: Egyptian???? Experience: 7+ years<br>???? About the Role<br>We are seeking a Senior Data Science Consultant – Cards Marketing Analytics to join our client engagement in Egypt. This role is pivotal in leveraging advanced analytics and predictive modeling to drive marketing strategies for credit and debit card portfolios. You will collaborate with client teams to deliver actionable insights that enhance spend growth, improve retention, and reduce churn.<br>???? Key Responsibilities Build predictive models for customer targeting, spend growth, retention, and churn reduction. Develop customer segmentations to support lifecycle marketing, campaign strategy, and personalization. Analyze campaign performance across segments, products, channels, and behaviors. Design test-and-learn frameworks including control groups and post-campaign reviews. Partner with client stakeholders to ensure outputs are practical, explainable, and business-ready.<br>✅ Requirements7–8 years of experience in data science / advanced analytics / consulting. Strong background in banking analytics, especially credit & debit cards. Expertise in marketing analytics, predictive modeling, segmentation, campaign analytics. Proficiency in Python, SAS, SQL with large banking datasets. Solid knowledge of statistical modeling, ML, model validation, performance tracking. Strong communication skills for senior-level presentations & reports. Consulting discipline: structured problem-solving, ownership, timely delivery. Comfortable working as a contractor in Egypt<br>???? Preferred Qualifications Based in Egypt (Egyptian) Experience in Egypt banking market. Exposure to card lifecycle analytics (acquisition, activation, usage, spend growth, retention, attrition). Familiarity with CRM, campaign management, marketing automation tools. Experience with A/B testing, uplift modeling, next-best-action, offer optimization, CLV models. Knowledge of cloud-based data platforms & modern analytics environments.<br>???? Apply Now: Send your CV to simmi@hiresquad.in

<div><span style="font-size: 11px;"><b>Job Overview</b></span></div><div><span style="font-size: 11px;">At Ecolab, we are committed to helping our customers achieve cleaner, safer, and healthier environments while driving operational excellence across our business. As an LDP Planning Analyst, you will play a key role in accelerating the digital transformation agenda across the Northwest Africa Supply Chain organization.</span></div><div><span style="font-size: 11px;"><br></span></div><div><span style="font-size: 11px;">This position combines supply chain analytics, process engineering, automation, and continuous improvement to enhance visibility, decision-making, and operational performance across multiple markets.</span></div><div><span style="font-size: 11px;"><br></span></div><div><span style="font-size: 11px;">What's in it for You?</span></div><div><span style="font-size: 11px;">Gain exposure to a regional supply chain organization spanning multiple countries.</span></div><div><span style="font-size: 11px;">Work with modern digital and analytics tools including Power BI, Power Platform, SQL, and automation technologies.</span></div><div><span style="font-size: 11px;">Lead impactful projects that improve service, inventory performance, and operational efficiency.</span></div><div><span style="font-size: 11px;">Partner with cross-functional teams across Supply Chain, Manufacturing, Quality, SHE, and Commercial functions.</span></div><div><span style="font-size: 11px;">Develop valuable experience in digital transformation, process excellence, and supply chain analytics within a global organization.</span></div><div><span style="font-size: 11px;">Contribute directly to Ecolab's long-term growth and operational excellence strategy.</span></div><div><span style="font-size: 11px;">What You Will Do</span></div><div><span style="font-size: 11px;">Supply Chain Analytics &amp; Reporting</span></div><div><span style="font-size: 11px;">Develop and maintain interactive Power BI dashboards to support business decision-making.</span></div><div><span style="font-size: 11px;">Analyze supply chain KPIs including inventory, service level, transportation performance, and operational efficiency.</span></div><div><span style="font-size: 11px;">Deliver insights that enable fact-based decisions and performance improvements across the region.</span></div><div><span style="font-size: 11px;">Automation &amp; Digital Solutions</span></div><div><span style="font-size: 11px;">Design and implement automated workflows using Power Automate and related tools.</span></div><div><span style="font-size: 11px;">Support data extraction, transformation, and integration from multiple systems including ERP and SQL databases.</span></div><div><span style="font-size: 11px;">Identify opportunities to digitize and simplify manual reporting and business processes.</span></div><div><span style="font-size: 11px;">Process Engineering &amp; Continuous Improvement</span></div><div><span style="font-size: 11px;">Lead and support process optimization initiatives focused on efficiency, quality, and cost improvement.</span></div><div><span style="font-size: 11px;">Conduct root cause analysis and implement sustainable corrective actions.</span></div><div><span style="font-size: 11px;">Support standardization of processes and best practices across operations.</span></div><div><span style="font-size: 11px;">Contribute to automation and digitalization projects that improve process control and visibility.</span></div><div><span style="font-size: 11px;">Develop and maintain process documentation, work instructions, and operating procedures.</span></div><div><span style="font-size: 11px;">Stakeholder Management</span></div><div><span style="font-size: 11px;">Collaborate with supply chain teams across Northwest Africa markets.</span></div><div><span style="font-size: 11px;">Partner with cross-functional stakeholders to align priorities and drive execution.</span></div><div><span style="font-size: 11px;">Present analysis, recommendations, and project progress to leadership teams.</span></div><div><span style="font-size: 11px;">Data Modelling</span></div><div><span style="font-size: 11px;">Build scalable data models supporting regional reporting and performance management.</span></div><div><span style="font-size: 11px;">Standardize metrics and reporting frameworks across multiple countries.</span></div><div><span style="font-size: 11px;">Minimum Qualifications</span></div><div><span style="font-size: 11px;">Bachelor's degree in industrial engineering, Supply Chain, Operations, Data Analytics, Information Systems, or a related field.</span></div><div><span style="font-size: 11px;">2-4 years of experience in Supply Chain Analytics, Process Engineering, Business Intelligence, Digital Transformation, or Continuous Improvement.</span></div><div><span style="font-size: 11px;">Experience using Power BI to build dashboards and data visualizations.</span></div><div><span style="font-size: 11px;">Strong analytical skills with advanced Microsoft Excel capabilities.</span></div><div><span style="font-size: 11px;">Experience working with ERP systems and large datasets.</span></div><div><span style="font-size: 11px;">Strong communication and stakeholder management skills.</span></div><div><span style="font-size: 11px;">Ability to work effectively in a fast-paced, multi-country environment.</span></div><div><span style="font-size: 11px;">Preferred Qualifications</span></div><div><span style="font-size: 11px;">Experience with Power Automate and Power Apps.</span></div><div><span style="font-size: 11px;">Knowledge of SQL and database management.</span></div><div><span style="font-size: 11px;">Python experience for analytics and automation.</span></div><div><span style="font-size: 11px;">Lean Six Sigma or continuous improvement background.</span></div><div><span style="font-size: 11px;">Experience in manufacturing, supply chain, or process-oriented industries.</span></div><div><span style="font-size: 11px;">Experience leading digital transformation or automation initiatives.</span></div><p><strong>Desired Candidate Profile</strong></p><p>Bachelor's degree in industrial engineering, Supply Chain, Operations, Data Analytics, Information Systems, or a related field. 2-4 years of experience in Supply Chain Analytics, Process Engineering, Business Intelligence, Digital Transformation, or Continuous Improvement. Experience using Power BI to build dashboards and data visualizations. Strong analytical skills with advanced Microsoft Excel capabilities. Experience working with ERP systems and large datasets. Strong communication and stakeholder management skills. Ability to work effectively in a fast-paced, multi-country environment. Preferred Qualifications Experience with Power Automate and Power Apps. Knowledge of SQL and database management. Python experience for analytics and automation. Lean Six Sigma or continuous improvement background. Experience in manufacturing, supply chain, or process-oriented industries. Experience leading digital transformation or automation initiatives.</p>

Valleysoft is a regional IT services provider delivering enterprise technology, application development, process management, and IT support services to clients around the world. Working across the Information Technology and Services sector, the company helps organizations build reliable, scalable digital solutions that support complex business and operational needs.<br><br>This role is an opportunity to contribute to modern data platform initiatives that power analytics and AI use cases across the enterprise. As a Data Engineer - Data Platforms (Databricks), you will play a central role in shaping data infrastructure, supporting cross-functional teams, and helping ensure data systems are performant, secure, and built to scale.<br><br>Responsibilities<br><br>Design, develop, and maintain scalable data pipelines for batch and real-time processing Build and optimize enterprise data platforms using Databricks and Apache Spark Develop ETL/ELT processes to ingest, transform, and integrate data from multiple sources Implement Delta Lake architecture and maintain data lake/lakehouse solutions Collaborate with Data Scientists, AI Engineers, Business Analysts, and application teams to support analytics and AI initiatives Optimize data storage, partitioning, and query performance Develop reusable data engineering frameworks and automation solutions Implement data quality, validation, lineage, and governance processes Ensure data security, privacy, and compliance with enterprise standards Monitor platform performance, troubleshoot production issues, automate deployment and infrastructure, contribute to architecture reviews, and maintain technical documentation and runbooks<br><br>Requirements<br><br>Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field6+ years of data engineering experience working with Databricks and Apache Spark Strong experience with Python and SQL, along with hands-on involvement in ETL/ELT processes Experience working with Delta Lake and cloud platforms Fluent in English Eligibility to work in Egypt

<section><p class="heading jdMain">Job Description</p><p class="heading">Roles &amp; Responsibilities</p><div class="paragraph"><p>Build and deploy production-grade Generative AI and Agentic AI solutions across the organization. Develop multi-agent systems and agent-to-agent (A2A) orchestration for autonomous, end-to-end workflows. Build RAG pipelines with vector databases and embeddings to ground LLMs in enterprise data. Design, train, and deploy Deep Learning models (NLP, CV, time-series) using PyTorch. Use AWS (Bedrock, SageMaker) and Azure (OpenAI, ML Studio) to host and scale AI workloads. Integrate Snowflake Cortex AI/ML, SAP Joule, and MuleSoft AI Chain with enterprise systems. Apply prompt engineering, function calling, and guardrails for reliable LLM apps. Operationalize models with MLOps/LLMOps: CI/CD, evaluation, monitoring, and responsible AI.</p><p>Key Responsibilities:</p><ul><li>Build LLM apps and agentic workflows using LangChain, LangGraph, LlamaIndex, AutoGen, or CrewAI.</li><li>Design agent-to-agent (A2A) orchestration: planning, tool use, memory, and multi-agent collaboration.</li><li>Develop RAG pipelines: chunking, embeddings, vector search, re-ranking, and grounding.</li><li>Train and fine-tune deep learning models with PyTorch.</li><li>Deploy models on AWS Bedrock, SageMaker, Azure OpenAI, and Azure ML Studio.</li><li>Integrate AI with Snowflake Cortex, SAP Joule, and MuleSoft AI Chain.</li><li>Apply prompt engineering, evaluation, and guardrails for safe, accurate outputs.</li><li>Implement MLOps/LLMOps: experiment tracking, CI/CD, monitoring, and drift detection.</li><li>Collaborate with engineering, data, and business teams and document architectures.</li></ul><p>Deliverables:</p><ul><li>Production GenAI and agentic applications adopted by business users.</li><li>Working multi-agent systems with A2A orchestration automating key workflows.</li><li>Reliable RAG pipelines with accurate, grounded LLM responses.</li><li>Trained and deployed deep learning models meeting accuracy, latency, and cost targets.</li><li>Successful integrations with Snowflake Cortex, SAP Joule, and MuleSoft AI Chain.</li><li>End-to-end MLOps/LLMOps pipelines for training, deployment, and monitoring.</li><li>Responsible AI guardrails ensuring quality, safety, and governance.</li><li>Reusable AI components, prompt libraries, and reference architectures.</li><li>Clear technical documentation and architecture diagrams.</li><li>Measurable business outcomes: efficiency, automation, and better user experience.</li></ul></div></section><section><p class="heading">Desired Candidate Profile</p><p class="paragraph"></p><ul><li>5+years of experience</li><li>Bachelor's degree in Computer Science, AI, Data Science, Software Engineering, or Mathematics.</li><li>Certifications in AWS, Azure, Snowflake, GenAI, or ML preferred.</li><li>Equivalent hands-on AI/ML experience may substitute for certifications.</li><li>Mandatory Technical Skills:</li><li>Strong Python with NumPy, Pandas, scikit-learn, PyTorch, TensorFlow, Hugging Face.</li><li>Hands-on with LLM and agent frameworks: LangChain, LangGraph, LlamaIndex, AutoGen, CrewAI.</li><li>Experience designing agent-to-agent (A2A) orchestration: tool use, planning, function calling, memory.</li><li>Practical RAG experience with vector DBs (Pinecone, Weaviate, Chroma, FAISS, pgvector).</li><li>Solid Deep Learning: transformers, CNNs, RNNs, fine-tuning, and model evaluation.</li><li>Hands-on with AWS AI/ML: Bedrock, SageMaker, Lambda, S3.</li><li>Hands-on with Azure AI/ML: Azure OpenAI, ML Studio, AI Foundry.</li><li>Good experience with Snowflake AI/ML: Cortex AI and Snowpark ML.</li><li>Good experience with SAP Joule: GenAI copilot and SAP integrations.</li><li>Good experience with MuleSoft AI Chain on Anypoint Platform.</li><li>Proficient in prompt engineering, evaluation, and guardrails.</li><li>Experience with REST APIs, Git, Docker, and CI/CD for models.</li><li>Solid MLOps/LLMOps: tracking, versioning, monitoring, responsible AI.</li><li>Strong analytical, problem-solving, and communication skills.</li></ul><p>Tools and Technologies:</p><ul><li>Languages &amp; Frameworks: Python, PyTorch, TensorFlow, Hugging Face, scikit-learn, FastAPI.</li><li>LLM &amp; Agent Frameworks: LangChain, LangGraph, LlamaIndex, AutoGen, CrewAI, Semantic Kernel.</li><li>LLM Providers: OpenAI, Anthropic Claude, Llama, Mistral, Cohere, Hugging Face.</li><li>Cloud AI: AWS Bedrock, SageMaker, Azure OpenAI, Azure ML Studio, AI Foundry.</li><li>Enterprise AI: Snowflake Cortex &amp; Snowpark ML, SAP Joule, MuleSoft AI Chain.</li><li>Vector DBs: Pinecone, Weaviate, Chroma, FAISS, pgvector, Milvus.</li><li>Data &amp; Storage: Snowflake, SQL, PostgreSQL, MongoDB, S3, Azure Data Lake, Pandas, Spark.</li><li>MLOps/LLMOps: MLflow, Weights &amp; Biases, LangSmith, LangFuse, Docker, Kubernetes, Git CI/CD.</li><li>Evaluation: RAGAS, DeepEval, TruLens, Arize.</li><li>Collaboration: Jupyter, VS Code, Jira, Confluence, Postman.</li></ul><p></p></section>

???? Senior Data Science Consultant – Cards Marketing Analytics???? Location: Egypt (Onsite – Client Office)???? Term: 12 months???? Eligibility: Egyptian???? Experience: 7+ years<br>???? About the Role<br>We are seeking a Senior Data Science Consultant – Cards Marketing Analytics to join our client engagement in Egypt. This role is pivotal in leveraging advanced analytics and predictive modeling to drive marketing strategies for credit and debit card portfolios. You will collaborate with client teams to deliver actionable insights that enhance spend growth, improve retention, and reduce churn.<br>???? Key Responsibilities Build predictive models for customer targeting, spend growth, retention, and churn reduction. Develop customer segmentations to support lifecycle marketing, campaign strategy, and personalization. Analyze campaign performance across segments, products, channels, and behaviors. Design test-and-learn frameworks including control groups and post-campaign reviews. Partner with client stakeholders to ensure outputs are practical, explainable, and business-ready.<br>✅ Requirements7–8 years of experience in data science / advanced analytics / consulting. Strong background in banking analytics, especially credit & debit cards. Expertise in marketing analytics, predictive modeling, segmentation, campaign analytics. Proficiency in Python, SAS, SQL with large banking datasets. Solid knowledge of statistical modeling, ML, model validation, performance tracking. Strong communication skills for senior-level presentations & reports. Consulting discipline: structured problem-solving, ownership, timely delivery. Comfortable working as a contractor in Saudi Arabia.<br>???? Preferred Qualifications Based in Egypt (Egyptian) Experience in Egypt banking market. Exposure to card lifecycle analytics (acquisition, activation, usage, spend growth, retention, attrition). Familiarity with CRM, campaign management, marketing automation tools. Experience with A/B testing, uplift modeling, next-best-action, offer optimization, CLV models. Knowledge of cloud-based data platforms & modern analytics environments.<br>???? Apply Now: Send your CV to simmi@hiresquad.in

Black Stone e IT is seeking an experienced and visionary AI Team Lead to oversee and guide our artificial intelligence initiatives. As the AI Team Lead, you will be responsible for leading a team of AI engineers and data scientists to develop innovative AI solutions that drive business growth and enhance user experiences. You will collaborate with cross-functional stakeholders to design and implement cutting-edge AI technologies and ensure successful project delivery.<br><br>Key Responsibilities:<br><br>Lead, mentor, and manage a team of AI engineers and data scientists Design and develop scalable AI models and algorithms tailored to business needs Collaborate with product managers, software developers, and business stakeholders to define AI project requirements Ensure rigorous testing, validation, and deployment of AI solutions Stay current with the latest advancements in AI, machine learning, and data science technologies Establish best practices and standards for AI development within the team Identify opportunities for AI integration to improve products and services<br><br>Requirements<br><br>Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or related field At least 8 years of experience in AI, machine learning, or data science roles Proven leadership experience managing technical teams Strong proficiency in programming languages such as Python, R, or Java Experience with machine learning frameworks like Tensor Flow, PyTorch, or Scikit-learn Solid understanding of data processing, feature engineering, and statistical modeling Familiarity with cloud platforms (AWS, Azure, or Google Cloud) for AI deployment Excellent problem-solving, analytical, and communication skills Ability to translate complex AI concepts into actionable business solutions<br><br>Benefits<br><br>Paid Time Off Performance Bonus Training & Development

The Cloud Engineer - OCI is responsible for providing advanced technical support and troubleshooting for Oracle Cloud Infrastructure (OCI) environments. The role acts as a key escalation point for complex technical issues raised by Level 1 support engineers, ensuring timely resolution while maintaining high service standards and adherence to operational processes.<br><br>Working closely with customers, internal engineering teams, and Oracle support services, the engineer assists in diagnosing and resolving issues related to cloud infrastructure, networking, security, and platform services. The role also contributes to the development of technical documentation, knowledge sharing across the support team, and the continuous improvement of support processes to enhance service delivery and customer satisfaction.<br><br>Responsibilities:<br><br>Handle escalated technical issues from L1 engineers Provide advanced troubleshooting for OCI services and architectures Create and maintain technical documentation and runbooks Mentor L1 engineers and conduct knowledge transfer sessions Identify patterns in customer issues and propose solutions Collaborate with OCI service teams on complex customer cases Participate in customer Well-Architected Reviews<br><br>Requirements<br><br>Oracle Cloud Infrastructure Certified Architect Professional (required) and one additional OCI certification2+ years of experience with OCI services in another MSP or vendor support role Strong knowledge of networking concepts and security best practices Experience with infrastructure as code (Terraform/Ansible) Proficiency in at least one programming/scripting language (Python, Shell scripting, etc.) Advanced Linux/Windows troubleshooting skills Bachelor's degree in Computer Science or related field Strong problem-solving and analytical abilities Excellent customer service orientation Ability to work in a fast-paced environment Good time management and prioritization skills Team player with strong collaboration abilities

Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and design appropriate solutions Work closely with IT and infrastructure teams to deploy and maintain data storage and processing systems, including databases, data warehouses, and cloud infrastructure Design, build, and maintain robust, scalable data pipelines to ingest, process, and transform data from various sources, including internal databases and external APIsOptimize data pipelines for performance, scalability, and reliability, ensuring timely and accurate delivery of data Implement data validation and quality checks to identify and rectify any issues in data pipelines, ensuring data integrity Explore and evaluate new technologies, tools, and frameworks to improve data engineering processes and capabilities Perform data modeling and schema design to support analytical and reporting requirements Design and build data marts and business layers to facilitate efficient data access and analysis<br><br>Requirements<br><br>Bachelor's degree in Computer Science, Information Systems, or other related technical field or equivalent work Proven experience as a Data engineer or similar role, with at least 4 years of experience Advanced SQL knowledge/experience - complex queries and query optimization Proficiency in programming languages such as Python Experienced in the development of data warehouses and proficient in data modeling Familiarity with cloud platforms such as AWS, Azure, or Google Cloud Platform Experience in building data streams using technologies such as Kafka, Flink, or Spark Streaming is considered a plus Strong problem-solving skills and attention to detail The ability and willingness to learn new technologies on the job Self driven, highly motivated, fast learner, ambitious and creative

About Turing:Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L.<br><br>Role Overview:Reviewing AI training problems and research environments built for a frontier AI lab Assessing whether problems are scientifically realistic, well-designed, and correctly graded — not solving them yourself Each task takes 30–90 minute<br>s<br>Requirements:Master's degree, PhD, or 4+ years of professional experience in one or more of the following fields (this is a must have requirement) Mechanical Engineering Materials Science Phylogenetics Computer Science (AI/ML) Knowledge of python programming language. Note: all qualified candidates will go through a background verification process, so please make sure your answers reflect credentials and experience you can document Ability to start immediately Feedback Skills: Ability to provide constructive feedback and detailed annotations. Communication: Excellent structured communication and collaboration skills in a remote setting. Independence: Self-motivated and able to work independently in a remote setting. Technical Setup: Desktop/Laptop set up with a good internet connectio<br>n.<br>Perks of Freelancing With Turing:Work in a fully remote environment Opportunity to work on cutting-edge AI projects with leading LLM companies Potential for contract extension based on performance and project ne<br>eds<br>Offer Details:Engagement type : Contractor assignment/freelancer (no medical/paid le<br>ave)

Role Description This is a full-time, on-site Senior Odoo role based in 6th of October. The Senior Odoo professional will design, develop, and implement Odoo modules and customizations that support core business processes such as sales, inventory, accounting, HR, and operations. Responsibilities include gathering and analyzing business requirements, configuring Odoo applications, writing clean and efficient code, and ensuring system stability and performance. The role involves troubleshooting issues, performing upgrades and integrations with third-party systems, and optimizing workflows to improve efficiency and data accuracy. The Senior Odoo professional will collaborate closely with cross-functional teams, provide user training and documentation, and contribute to ongoing process and system improvements. Qualifications Strong experience with Odoo development and customization, including Python programming and Odoo framework knowledge. Proficiency in configuring and managing core Odoo modules (e.g., Sales, Inventory, Accounting, HR, CRM, Manufacturing). Experience with relational databases (e.g., Postgre SQL), data modeling, and performance optimization. Knowledge of APIs and integration methods to connect Odoo with external systems and services. Solid understanding of business processes in ERP environments and ability to translate requirements into technical solutions. Ability to analyze, troubleshoot, and resolve system and application issues effectively. Strong communication and collaboration skills, with the ability to work with technical and non-technical stakeholders. Experience leading or mentoring junior team members in Odoo or ERP projects is highly beneficial. Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related field (or equivalent practical experience). Experience in on-site ERP implementations and user training, preferably within industrial or commercial sectors.

About Turing:Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L.<br><br>Role Overview:Reviewing AI training problems and research environments built for a frontier AI lab Assessing whether problems are scientifically realistic, well-designed, and correctly graded — not solving them yourself Each task takes 30–90 minute<br>s<br>Requirements:Master's degree, PhD, or 4+ years of professional experience in one or more of the following fields (this is a must have requirement) Mechanical Engineering Materials Science Phylogenetics Computer Science (AI/ML) Knowledge of python programming language. Note: all qualified candidates will go through a background verification process, so please make sure your answers reflect credentials and experience you can document Ability to start immediately Feedback Skills: Ability to provide constructive feedback and detailed annotations. Communication: Excellent structured communication and collaboration skills in a remote setting. Independence: Self-motivated and able to work independently in a remote setting. Technical Setup: Desktop/Laptop set up with a good internet connectio<br>n.<br>Perks of Freelancing With Turing:Work in a fully remote environment Opportunity to work on cutting-edge AI projects with leading LLM companies Potential for contract extension based on performance and project ne<br>eds<br>Offer Details:Engagement type : Contractor assignment/freelancer (no medical/paid le<br>ave)

<section><p class="heading jdMain">Job Description</p><p class="heading">Roles &amp; Responsibilities</p><div class="paragraph"><p>Business insight and decision support: Translate strategic and operational questions into clear analyses, dashboards, reports, and recommendations for leadership and functional teams. KPI and metrics ownership: Define, document, and govern business metrics across fuel consumption, transaction activity, customer adoption, fleet performance, station coverage, invoicing, product usage, savings, churn, and operational efficiency. Dashboard and reporting delivery: Build reliable self-service dashboards for executives, product, sales, finance, operations, customer success, and country or regional teams. Customer and product analytics: Analyze user journeys, feature adoption, customer cohorts, fleet behavior, transaction trends, fuel limits, budget usage, and drop-off points to guide product and growth decisions. Operations and finance analytics: Support reconciliation, invoicing, station performance, wallet movement, service usage, cost analysis, revenue tracking, and profitability insights. Fraud and anomaly insight: Partner with product, operations, and data engineering to identify unusual fuel patterns, tampering indicators, policy exceptions, and monitoring rules that improve trust and control. Experimentation and forecasting: Design analyses for pilots, pricing, campaigns, product launches, and operational changes; support forecasting for consumption, transactions, customer demand, and station utilization. Data storytelling: Present insights clearly, explain trade-offs, quantify impact, and convert analysis into practical recommendations and action plans. Data quality partnership: Work with data engineering to improve source data, metric definitions, documentation, dashboard reliability, and analytics-ready datasets. Analytics mentorship: Set standards for analysis quality, dashboard design, metric governance, and stakeholder communication while mentoring less experienced analysts. Core analytics stack expectations The exact stack may evolve, but the successful candidate should be comfortable operating across the following categories: Analysis: SQL, spreadsheets, Python or R, notebooks, statistical methods, and business case modeling. BI and visualization: Power BI, Tableau, Looker, Metabase, Superset, or equivalent dashboarding tools. Data modeling: dimensional thinking, metric definitions, cohort tables, funnel tables, and curated analytical datasets. Collaboration: requirements gathering, stakeholder workshops, documentation, presentations, and decision memos. Governance: metric catalog, dashboard ownership, access control awareness, and data quality issue management. Product analytics: event data, customer journeys, feature usage, adoption metrics, retention, and conversion analysis. Competitive salary and benefits package. Opportunity to work on cutting-edge technology with a passionate team. Career growth and development opportunities. A collaborative and inclusive work environment.</p></div></section><section><p class="heading">Desired Candidate Profile</p><p class="paragraph"></p><ul><li>5+ years of experience in data analytics, business intelligence, product analytics, revenue analytics, operations analytics, or a similar analytical role.</li><li>Advanced SQL skills with the ability to independently extract, transform, join, validate, and analyze complex data from multiple domains.</li><li>Strong experience building dashboards and data products using Power BI, Tableau, Looker, Metabase, Superset, or similar BI tools.</li><li>Strong understanding of KPI design, metric definitions, funnel analysis, cohort analysis, segmentation, trend analysis, forecasting, and root-cause analysis.</li><li>Ability to convert ambiguous business questions into analytical plans, structured hypotheses, and actionable recommendations.</li><li>Experience working with transactional, product, customer, payment, operational, or financial datasets at scale.</li><li>Working knowledge of Python or R for analysis, automation, statistical exploration, or notebook-based research.</li><li>Excellent stakeholder management and communication skills, including the ability to explain technical findings to non-technical audiences.</li><li>Strong attention to data accuracy, definitions, documentation, and reproducibility.</li><li>Comfort working in fast-paced product and engineering environments with changing priorities and high ownership expectations.</li><li>Experience in fintech, fleet management, logistics, mobility, fuel, marketplace, SaaS, or high-volume transaction businesses.</li><li>Experience with dbt, semantic layers, data catalogs, metric stores, or analytics engineering workflows.</li><li>Familiarity with fraud analytics, anomaly detection, operational controls, pricing analysis, or customer savings measurement.</li><li>Experience with A/B testing, causal inference, retention analysis, churn prediction, LTV modeling, or commercial performance analytics.</li><li>Arabic and English business communication skills are a plus for regional stakeholder engagement.</li></ul><p></p></section>

About Turing:Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L.<br><br>Role Overview:Reviewing AI training problems and research environments built for a frontier AI lab Assessing whether problems are scientifically realistic, well-designed, and correctly graded — not solving them yourself Each task takes 30–90 minute<br>s<br>Requirements:Master's degree, PhD, or 4+ years of professional experience in one or more of the following fields (this is a must have requirement) Mechanical Engineering Materials Science Phylogenetics Computer Science (AI/ML) Knowledge of python programming language. Note: all qualified candidates will go through a background verification process, so please make sure your answers reflect credentials and experience you can document Ability to start immediately Feedback Skills: Ability to provide constructive feedback and detailed annotations. Communication: Excellent structured communication and collaboration skills in a remote setting. Independence: Self-motivated and able to work independently in a remote setting. Technical Setup: Desktop/Laptop set up with a good internet connectio<br>n.<br>Perks of Freelancing With Turing:Work in a fully remote environment Opportunity to work on cutting-edge AI projects with leading LLM companies Potential for contract extension based on performance and project ne<br>eds<br>Offer Details:Engagement type : Contractor assignment/freelancer (no medical/paid le<br>ave)

Develop and implement the data engineering strategy in line with our business objectives and industry best practices Lead, mentor, and grow a team of data engineers, fostering a culture of innovation, collaboration, and continuous improvement Collaborate with the Data Architect to design, build, and optimize data infrastructure, ensuring it is scalable, secure, and performant Work closely with other engineering managers to ensure seamless data integration and accessibility for analytics and business intelligence initiatives Establish and enforce data engineering standards, guidelines, and best practices across the organization Identify, evaluate, and implement new data technologies and tools to enhance the capabilities of the data team Collaborate with cross-functional teams to identify data requirements and support data-driven projects Monitor and maintain the health and performance of mylo's data ecosystem, proactively identifying and addressing any issues<br><br>Requirements<br><br>Bachelor's or Master's degree in Computer Science, Engineering, or a related field Minimum of 8 years of experience in data engineering, with at least 3 years in a leadership role Strong knowledge of data science tools, technologies, and best practices, including data warehousing, ETL, and data pipelines Proficiency in programming languages such as Python, Java, or Scala Experience with big data technologies such as Hadoop, Spark, and Kafka Familiarity with cloud-based data solutions (AWS, Azure, or Google Cloud) Exceptional problem-solving, communication, and leadership skills Ability to collaborate effectively with cross-functional teams and stakeholders<br><br>Benefits<br><br>Office environment: When you come to our b_labs office, you'll find creative workspaces and an open design to foster collaboration between teams.<br><br>Flexibility: You know best whether you want to work from home or in the office.<br><br>Equipment: From "Day 1" you will receive all the equipment you need be successful at work.

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span>Business insight and decision support: Translate strategic and operational questions into clear analyses, dashboards, reports, and recommendations for leadership and functional teams.<br> KPI and metrics ownership: Define, document, and govern business metrics across fuel consumption, transaction activity, customer adoption, fleet performance, station coverage, invoicing, product usage, savings, churn, and operational efficiency.<br> Dashboard and reporting delivery: Build reliable self-service dashboards for executives, product, sales, finance, operations, customer success, and country or regional teams.<br> Customer and product analytics: Analyze user journeys, feature adoption, customer cohorts, fleet behavior, transaction trends, fuel limits, budget usage, and drop-off points to guide product and growth decisions.<br> Operations and finance analytics: Support reconciliation, invoicing, station performance, wallet movement, service usage, cost analysis, revenue tracking, and profitability insights.<br> Fraud and anomaly insight: Partner with product, operations, and data engineering to identify unusual fuel patterns, tampering indicators, policy exceptions, and monitoring rules that improve trust and control.<br> Experimentation and forecasting: Design analyses for pilots, pricing, campaigns, product launches, and operational changes; support forecasting for consumption, transactions, customer demand, and station utilization.<br> Data storytelling: Present insights clearly, explain trade-offs, quantify impact, and convert analysis into practical recommendations and action plans.<br> Data quality partnership: Work with data engineering to improve source data, metric definitions, documentation, dashboard reliability, and analytics-ready datasets.<br> Analytics mentorship: Set standards for analysis quality, dashboard design, metric governance, and stakeholder communication while mentoring less experienced analysts.<br> Competitive salary and benefits package.<br> Opportunity to work on cutting-edge technology with a passionate team.<br> Career growth and development opportunities.<br> A collaborative and inclusive work environment.<br> Required qualifications 5+ years of experience in data analytics, business intelligence, product analytics, revenue analytics, operations analytics, or a similar analytical role.<br> Advanced SQL skills with the ability to independently extract, transform, join, validate, and analyze complex data from multiple domains.<br> Strong experience building dashboards and data products using Power BI, Tableau, Looker, Metabase, Superset, or similar BI tools.<br> Strong understanding of KPI design, metric definitions, funnel analysis, cohort analysis, segmentation, trend analysis, forecasting, and root-cause analysis.<br> Ability to convert ambiguous business questions into analytical plans, structured hypotheses, and actionable recommendations.<br> Experience working with transactional, product, customer, payment, operational, or financial datasets at scale.<br> Working knowledge of Python or R for analysis, automation, statistical exploration, or notebook-based research.<br> Excellent stakeholder management and communication skills, including the ability to explain technical findings to non-technical audiences.<br> Strong attention to data accuracy, definitions, documentation, and reproducibility.<br> Comfort working in fast-paced product and engineering environments with changing priorities and high ownership expectations.<br> Preferred qualifications Experience in fintech, fleet management, logistics, mobility, fuel, marketplace, SaaS, or high-volume transaction businesses.<br> Experience with dbt, semantic layers, data catalogs, metric stores, or analytics engineering workflows.<br> Familiarity with fraud analytics, anomaly detection, operational controls, pricing analysis, or customer savings measurement.<br> Experience with A/B testing, causal inference, retention analysis, churn prediction, LTV modeling, or commercial performance analytics.<br> Arabic and English business communication skills are a plus for regional stakeholder engagement.<br> Core analytics stack expectations The exact stack may evolve, but the successful candidate should be comfortable operating across the following categories: Analysis: SQL, spreadsheets, Python or R, notebooks, statistical methods, and business case modeling.<br> BI and visualization: Power BI, Tableau, Looker, Metabase, Superset, or equivalent dashboarding tools.<br> Data modeling: dimensional thinking, metric definitions, cohort tables, funnel tables, and curated analytical datasets.<br> Collaboration: requirements gathering, stakeholder workshops, documentation, presentations, and decision memos.<br> Governance: metric catalog, dashboard ownership, access control awareness, and data quality issue management.<br> Product analytics: event data, customer journeys, feature usage, adoption metrics, retention, and conversion analysis.<br></span> </div>

<section><p class="heading jdMain">Job Description</p><p class="heading">Roles &amp; Responsibilities</p><div class="paragraph"><p>As the leading delivery company in the region, we have a great responsibility and opportunity to impact the lives of millions of customers, restaurant partners, and riders. To realize our potential, we need to advance our platform to become much more intelligent in how it understands and serves our users.</p><p>As a n Analytics Engineer, you will be responsible for transforming raw data into well-structured, reliable, and accessible data models that enable analysts, data scientists, and business stakeholders to make informed decisions. You will work closely with data engineers to build scalable data pipelines and collaborate with analysts to ensure data is actionable and insightful.</p><p>Design, build, and maintain clean, efficient, and scalable data models in SQL and dbt.</p><p>Optimize query performance and data processing efficiency.</p><p>Ensure data is structured to support self-service analytics and business intelligence.</p><p>Work closely with data engineers to define data requirements and enhance ETL pipelines.</p><p>Partner with product analysts, data scientists, and business teams to ensure data meets analytical and reporting needs.</p><p>Implement and enforce data quality best practices to ensure accuracy and consistency.</p><p>Develop and maintain data transformation workflows using dbt, SQL, and cloud-based data platforms.</p><p>Automate data validation and reporting processes.</p><p>Monitor data integrity and troubleshoot data issues proactively.</p><p>Advocate for best practices in documentation, testing, and version control.</p></div></section><section><p class="heading">Desired Candidate Profile</p><p class="paragraph"></p><ul><li>Bachelor's degree in engineering, computer science, technology, or similar fields. A postgraduate degree is a plus but not required.</li><li>Strong proficiency in Python, SQL and experience with dbt for data modeling.</li><li>Experience working with cloud-based data warehouses (e.g., Snowflake, BigQuery, GCP, Redshift).</li><li>Familiarity with version control (Git) and CI/CD practices for data workflows.</li><li>Understanding of data engineering principles, including ETL/ELT processes.</li></ul><p></p></section>

Egy Bell is hiring Solution Delivery Engineer ( 6 months project) for a multinational telecommunications company. Key Responsibilities• Lead the technical delivery of infrastructure and software solutions from implementation through production handover.• Design, implement, and maintain CI/CD pipelines and Git Ops-based delivery frameworks to ensure scalable, repeatable, and auditable deployments.• Build, administer, and support Linux-based environments (RHEL / Oracle Linux), Kubernetes clusters (Rancher preferred), and cloud-hosted infrastructure.• Manage containerized workloads, image repositories, runtime configurations, and lifecycle operations.• Perform deep technical troubleshooting across infrastructure, operating systems, middleware, applications, and integrations.• Implement monitoring, observability, alerting, and operational readiness standards across deployed solutions.• Drive automation initiatives through scripting and Infrastructure-as-Code practices, reducing manual effort and increasing delivery efficiency.• Ensure compliance with security, governance, vulnerability management, and platform hardening requirements.• Produce high-quality technical documentation, deployment guides, operational runbooks, and handover packages. Required Qualifications• Bachelor's degree in Computer Science, Engineering, or a related discipline.• Minimum 5 years of experience in Solution Delivery, Platform Engineering, Dev Ops, Infrastructure Engineering, or a similar technical role.• Excellent English communication skills.• Linux Administration (RHEL, Oracle Linux)• Kubernetes Administration & Rancher• Container Technologies and Lifecycle Management• Cloud Platforms (AWS, Azure, GCP, or Private Cloud)• CI/CD Pipelines (Git Lab CI, Jenkins, Argo CD, or equivalent)• Git Ops Methodologies• Infrastructure as Code (Terraform, Ansible, Helm)• Bash and/or Python Scripting• Monitoring & Observability Tools (Prometheus, Grafana, ELK)• Root Cause Analysis & Full-Stack Troubleshooting• Security Hardening, Vulnerability Management & Compliance• Experience with Service Mesh, Ingress Controllers, and Network Policies within Kubernetes environments.• Exposure to regulated or compliance-driven environments.• Familiarity with ITSM and Change Management processes.• Contribution to Open-Source projects or communities is considered an advantage

Position: STEM - Maths Expert (Task Based) Type: Short-Term Contract (3 months) Compensation: $250 per task upon approval Location: Remote Commitment: At least 4 hours per day and up to 40 hours per week with 4 hours overlap with PST<br>Role Responsibilities Develop and apply advanced mathematical models and computational techniques to solve complex problems across various mathematical domains Collaborate with multidisciplinary teams to contribute mathematical insight and expertise to research projects Engage with the latest mathematical literature, including cutting-edge research papers Design and solve advanced mathematical reasoning problems for AI model evaluation and training Contribute to mathematical benchmarking and problem-solving workflows for large language models Analyze complex mathematical concepts and provide structured, rigorous solutions Support evaluation initiatives focused on advanced reasoning and applied mathematics<br>Requirements Master s or PhD in Mathematics or a closely related field Strong expertise in at least 4 of the following areas: computable functions and mathematical logic, algebra and number theory, linear algebra and matrix theory, topology and geometry, analysis, probability and statistics, and applied mathematics Demonstrated ability to solve complex mathematical problems through research, publications, or projects Excellent analytical and critical thinking skills with strong attention to detail Strong communication skills with the ability to explain complex mathematical concepts clearly Collaborative mindset with experience working in multidisciplinary teams Python and data analysis experience is desirable but not mandatory Access to a desktop or laptop with a reliable internet connection Linked In profile is mandatory in the resume Candidates will undergo a background verification process after onboarding<br>Application Process Apply/Easy Apply and check email for application form Fill Google form Assessment Link (After shortlisting to be completed within 24 hours)<br><br>Skills: mathematician