Job Description:

We are seeking a highly skilled and experienced Data Scientists Team Lead with a strong background in Generative AI (GEN AI) to join our dynamic team at Smart Vision. The ideal candidate will have a proven track record of leading data science teams, developing advanced AI models, and implementing GEN AI solutions in real-world applications.

 

Responsibilities:

• Lead and manage a team of data scientists, fostering a collaborative and high-performing environment.
• Define and prioritize data science projects aligned with Smart Vision's strategic goals.
• Translate business needs into technical problems and design data-driven solutions leveraging computer vision and AI methodologies.
• Develop and implement innovative algorithms utilizing traditional and Generative AI (GEN AI) techniques to enhance Smart Vision's products and services.
• Collaborate with cross-functional teams to integrate AI solutions into products and services, ensuring alignment with business objectives.
• Oversee the entire data science lifecycle, including data acquisition, cleaning, exploration, model development, training, and evaluation..
• Drive the end-to-end lifecycle of data science projects, from data collection and preprocessing to model development, evaluation, and deployment.
• Communicate complex technical concepts to both technical and non-technical audiences.
• Stay up-to-date with the latest advancements in data science, computer vision, and GEN AI, and actively seek opportunities for continuous learning and improvement.
• Mentor and coach junior data scientists, fostering their professional development.
• Stay updated with the latest advancements in AI and machine learning, and incorporate relevant technologies and methodologies into projects.
• Ensure the quality and performance of AI models through rigorous testing and validation.

Qualifications:Master’s or PhD in Computer Science, Data Science, Statistics, or a related field.Minimum of 5+ years of experience in a data science position leading and +2 Years of experience managing a data science team.Proven experience in developing and implementing computer vision and AI solutions.Strong understanding of machine learning algorithms, deep learning architectures, and statistical analysis techniques.In-depth knowledge and practical experience with Generative AI (GEN AI) techniques.Excellent communication, collaboration, and problem-solving skills.Ability to prioritize tasks, manage multiple projects, and meet deadlines effectively.Experience working in an agile development environment is a plus.Proven experience leading and managing data science teams.Proficiency in programming languages such as Python, R, or similar.Hands-on experience with AI/ML frameworks and libraries such as TensorFlow, PyTorch, scikit-learn, etc.Strong analytical and problem-solving skills, with the ability to work with large and complex datasets.Excellent communication and leadership skills.Familiarity with cloud platforms (AWS, Azure, GCP) is a plus. Demonstrable experience leveraging data driven models and implementing machine learning models; from initial conception right through to the final productionalised model (analyzing and interpreting data, drawing conclusions, defining recommended actions, and reporting results across diverse stakeholders). • Ability to combine business intuition with the application of advanced solutions • Deep and broad statistical modelling expertise in various domains • Ability to test hypotheses from raw datasets and draw meaningful conclusions • Significant experience in Big Data analytics & deployment of models and algorithms into a commercial/consumer environment to analyse extremely large volumes of data • Excellent communication skills, with proven ability to work cross functional teams to translate business issues into potential analytics solutions and communicate complex findings in a structured and clear manner to a non-technical audience • A curious mind, self-starter and passion for keeping up with the latest in Data Science and Machine Learning communities • Experience with statistical data analysis (e.g., a/b tests, hypothesis testing, experiment design) • Knowledge of various Neural Network architectures (RNN, CNN, attention/transformer) • Knowledge of modern NLP techniques such as transfer learning (ELMo, ULMFiT, BERT) • Experience in data manipulation and statistical analysis using Python, R, Scala. • Experience with statistical analysis tools such as SPSS, SAS, STATA, etc. • Experience with scripting in Python packages such as NumPy, SciPy, pandas, scikit-learn, dplyr, ggplot2. • Machine learning Libraries – Spark ML, xgboost, Tensorflow + Keras, GraphFrames • Familiar with leading visualisation tools (e.g. Tableau, PowerBI, Cognos, Qlikview, Spotfire, D3.js) • Experience in Big Data Analytics landscape and technology trends (e.g. Spark, Hadoop, NoSQL, SQL) • PhD/MSc in a quantitative field such as Artificial Intelligence/Computer Science or other such related field is preferred.  Preferred Qualifications:Experience in natural language processing (NLP), computer vision, or other AI subfields.Demonstrated success in deploying AI solutions in a business environment.Publications or contributions to AI research communities.