Actuarial Data Scientist
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Key skills for this role
About the Role
Who Are We HALA is a leading fintech player in the MENAP region that aims to redefine financial services and build the future bank of SMEs. HALA aims at empowering SMEs to start.
Key Skills for This Role
Responsibilities
- Build, validate, and improve models for probability of default, credit scoring, affordability, delinquency prediction, and customer risk segmentation
- Analyze historical repayment behavior, first payment failure, delinquency trends, vintage curves, and default patterns
- Support the enhancement of Hala Financing's credit engine by identifying stronger predictive variables and decision rules
- Develop early warning indicators to detect customers likely to delay, default, or underperform
- Monitor portfolio performance across cohorts, channels, customer segments, loan products, tenure, ticket size, and repayment behavior
- Build dashboards and analytical frameworks to track approval quality, disbursement performance, default rates, roll rates, collections performance, and portfolio risk
- Run scenario analysis and stress testing to assess the impact of growth, pricing, approval policy, and macroeconomic changes on portfolio performance
- Support management reporting for credit performance, investor reporting, and internal risk committees
- Use statistical and machine learning techniques to improve credit decisioning and default prediction
- Work with structured and alternative data sources, including transaction data, merchant behavior, repayment history, business activity, and external data
- Design experiments and champion/challenger tests to evaluate credit policy changes
- Partner with Data Engineering to improve data quality, feature availability, model monitoring, and automation
Requirements
- Experience in credit risk modelling, including probability of default, credit scoring, affordability, delinquency prediction, and customer risk segmentation
- Strong statistical and machine learning skills
- Ability to analyze historical repayment behavior, delinquency trends, vintage curves, and default patterns
- Experience with portfolio monitoring and building dashboards
- Business judgment and ability to translate data insights into practical business actions
Full Job Posting
Role Summary
- Hala Financing is looking for an Actuarial Data Scientist to join the Data team and support the development of our credit engine, risk models, and portfolio monitoring capabilities.
- The role will focus on predicting probability of default, improving credit decisioning, enhancing risk segmentation, and building data driven models that support responsible growth in SME lending.
- The ideal candidate combines actuarial thinking, credit risk modelling, machine learning, and strong business judgment.
Key Responsibilities Credit Risk Modelling
- Build, validate, and improve models for probability of default, credit scoring, affordability, delinquency prediction, and customer risk segmentation
- Analyze historical repayment behavior, first payment failure, delinquency trends, vintage curves, and default patterns
- Support the enhancement of Hala Financing's credit engine by identifying stronger predictive variables and decision rules
- Develop early warning indicators to detect customers likely to delay, default, or underperform
Key Responsibilities Portfolio Analytics
- Monitor portfolio performance across cohorts, channels, customer segments, loan products, tenure, ticket size, and repayment behavior
- Build dashboards and analytical frameworks to track approval quality, disbursement performance, default rates, roll rates, collections performance, and portfolio risk
- Run scenario analysis and stress testing to assess the impact of growth, pricing, approval policy, and macroeconomic changes on portfolio performance
- Support management reporting for credit performance, investor reporting, and internal risk committees
Key Responsibilities Data Science & Machine Learning
- Use statistical and machine learning techniques to improve credit decisioning and default prediction
- Work with structured and alternative data sources, including transaction data, merchant behavior, repayment history, business activity, and external data where available
- Design experiments and champion/challenger tests to evaluate credit policy changes
- Partner with Data Engineering to improve data quality, feature availability, model monitoring, and automation
Key Responsibilities Business Partnership
- Work closely with Credit, Risk, Product, Collections, Finance, and Business teams to translate business questions into analytical solutions
- Provide clear recommendations on credit policy, approval rules, risk appetite, and portfolio growth
- Help balance growth, profitability, and risk by turning data insights into practical business actions
What We Offer You
- Inclusive and diverse culture that encourages innovation and flexibility in remote, in office, and hybrid work setups
- Highly competitive compensation packages, including the potential for shares
- Regular training and an annual learning stipend
- Opportunity to work with a talented team of over 30 nationalities in 7 countries
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