Head of Data Science

About the Role

We are partnering with an innovative financial services organization to appoint a Head of Data Science to be based in Dubai, UAE. This is a strategic leadership opportunity to build and scale an in-house credit technology capability that powers digital lending across a growing wallet ecosystem. This role is ideal for a highly analytical and commercially minded leader with deep expertise in credit risk modelling, digital lending, machine learning, and automated credit decisioning.

About the Requirements

• Bachelor's Degree in: Mathematics, Statistics, Computer Science, Data Science, Economics, Engineering, Quantitative Finance, Related quantitative disciplines
• Master's Degree preferred
• 7 - 10 years of experience in: Credit Risk, Decision Science, Data Science, Machine Learning, Consumer Lending, Financial Services Analytics
• Proven experience developing and deploying: Credit scoring models, Behavioural risk models, Consumer lending models, Automated credit decision systems
• Strong understanding of: Probability of Default (PD), Credit risk grading, Eligibility frameworks, Affordability methodologies, Credit policy design, Credit limit management
• Experience working with large-scale transactional, wallet, customer, or alternative datasets
• Advanced proficiency in: Python, SQL
• Strong knowledge of machine learning techniques including Logistic Regression, Scorecards, Gradient Boosting, XGBoost, LightGBM
• Experience managing models throughout the entire lifecycle from development and validation through deployment and monitoring
• Should have experience of West Africa markets

About You

• Credit Scoring & Decisioning: Lead the end-to-end development and enhancement of the Credit Scoring & Decision Engine
• Design and deploy: Credit scoring models, Risk grading frameworks, Probability of Default (PD) models, Eligibility engines, Affordability assessments, Credit limit management strategies
• Develop application and behavioural credit risk models
• Establish model validation, monitoring, governance, explainability, and auditability frameworks
• Drive ongoing model optimization using portfolio performance insights
• Credit Limit & Affordability Strategy
• Own credit limit strategies including: Initial limit assignment, Maximum exposure limits, Limit increases and decreases, Customer retention strategies, Data & Technology Collaboration
• Define the integration framework between the Credit Scoring Engine and Loan Management System (LMS)

About the Recruiter

Contact: Jasmine Puno – Recruitment Resourcer

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