Responsible for credit risk analytics projects from banking, insurance, telco and e-com domains. Analytics projects can range from projects involving only simple analysis or predictive analytics but not limited to these varieties of work.
| Daily Operations: |
- Read data appropriately from different file format and run data sanity checks.
- Explore datasets and recommend actionable based on insights generated from the datasets.
- Automate set of codes for recurring activities/reporting.
- Statistical analysis and hypothesis testing.
- Develop, validate and implement credit risk models using statistical and non-statistical methodologies in alignment with CRIF approach and standards.
- Document the outcome of statistical/non-statistical outcome.
- Present the analysis to clients/internal stakeholders.
- Producing reports and charts communicating trends within data to non-specialists.
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Passionate about data and strong analytical and problem-solving skills.Good knowledge of statistical methodologies like Linear/Logistic regression, segmentation methodologies, Random Forest etc.Good at programming in one of the languages out of SAS, R, PythonPreferred Qualifications:Education: Bachelor/Masters in Statistics/Maths/Economics/Operation Research, Engineering from leading institutions, or equivalent to these degrees.Spoken Language: English (mandatory), Arabic (mandatory), French (preferable).5-6 years minimum experience in a Consulting/Banking/Technology firms. , PySparkGood interpersonal skills.Outstanding attention to detail.Proven ability to meet established deadlines.Quick learner and good at multitasking.Written and verbal communication skills.Proficient in MS Word, Excel, Access, and Power Point.