Actuarial Data Scientist📣 Job Ad

About Hala

Hala is a prominent fintech company operating across the MENAP region, focused on transforming financial services and developing the future bank for Small and Medium-sized Enterprises (SMEs). The company empowers SMEs with advanced financial and technological tools to facilitate their business operations and growth. Founded in 2017, Hala holds multiple entities in the UAE, Saudi Arabia, and Egypt, including HALA Payments and HALA Logistics, and is licensed by the Saudi Arabian Central Bank. This full-time position for an Actuarial Data Scientist is based in Riyadh.

The Actuarial Data Scientist Role

Hala Financing is seeking an Actuarial Data Scientist to join its Data team. This role is central to supporting the development of the company's credit engine, enhancing risk models, and strengthening portfolio monitoring capabilities. The focus will be on predicting the probability of default, refining credit decisioning processes, improving risk segmentation, and building data-driven models that contribute to responsible growth in SME lending. The ideal candidate will possess a strong combination of actuarial thinking, credit risk modelling expertise, machine learning proficiency, and sound business judgment.

Key Responsibilities

• Develop, validate, and enhance models for probability of default, credit scoring, affordability, delinquency prediction, and customer risk segmentation.
• Analyze historical repayment behavior, first-payment failure rates, delinquency trends, vintage curves, and default patterns.
• Contribute to the improvement of Hala Financing’s credit engine by identifying predictive variables and decision rules.
• Establish early-warning indicators to identify customers likely to delay payments, default, or underperform.
• Monitor portfolio performance across various cohorts, channels, customer segments, loan products, tenure, ticket size, and repayment behaviors.
• Construct dashboards and analytical frameworks to track approval quality, disbursement performance, default rates, roll rates, collections performance, and overall portfolio risk.
• Conduct scenario analysis and stress testing to evaluate the impact of growth strategies, pricing adjustments, approval policies, and macroeconomic changes on portfolio performance.
• Support management reporting for credit performance, investor reporting, and internal risk committees.
• Apply statistical and machine learning techniques to optimize 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 and execute experiments and champion/challenger tests to assess the effectiveness of credit policy changes.
• Collaborate with the Data Engineering team to enhance data quality, feature availability, model monitoring, and automation.
• Partner with Credit, Risk, Product, Collections, Finance, and Business teams to translate business questions into analytical solutions.
• Provide clear, data-driven recommendations on credit policy, approval rules, risk appetite, and portfolio growth strategies.
• Help balance growth, profitability, and risk by converting data insights into actionable business strategies.

Required Qualifications and Experience

• 5-10 years of professional experience in a relevant actuarial, data science, or credit risk modelling role.
• Demonstrated expertise in credit risk modelling, probability of default, and risk segmentation.
• Proficiency in statistical analysis and machine learning techniques.
• Experience working with diverse data sources, including transactional and behavioral data.
• Strong analytical skills with the ability to translate complex data into clear business insights and recommendations.
• Solid business judgment and the ability to collaborate effectively with cross-functional teams.

Impact and Success Factors

Success in this role will be measured by the ability to significantly improve the accuracy of default prediction and credit risk segmentation. Key indicators of achievement include a reduction in first-payment failures and early delinquency rates, alongside stronger credit engine decisioning and approval quality. The Actuarial Data Scientist will contribute to clear portfolio monitoring and the development of effective early-warning indicators, ultimately fostering a better balance between loan growth, risk, profitability, and capital efficiency for Hala Financing.

Work Environment

This is a full-time position based in Riyadh, Saudi Arabia, within a dynamic fintech environment. The role involves close collaboration with various internal teams, contributing directly to the strategic financial services offered to SMEs.