Head of Data Science & Credit Risk

About the role

The Head of Data Science & Credit Risk will lead the strategy for ML‑powered underwriting and credit decisioning across fast‑growing markets. Based in Turkey, you will own the full lifecycle of risk models, from development and deployment to monitoring and measurable business impact, while shaping credit policies and responsible lending practices.

Key responsibilities

• Design, test, deploy and continuously improve machine‑learning models for credit decisioning, fraud detection, risk segmentation and marketing attribution.
• Develop underwriting algorithms using alternative data to expand access while maintaining risk standards.
• Build and scale real‑time scoring models across multiple markets and products.
• Establish model governance, MLOps practices, and monitoring for accuracy, drift and performance.
• Define credit risk frameworks, policies, approval strategies and risk thresholds for each market.
• Lead portfolio monitoring, stress testing, and expected credit loss modeling in partnership with Finance.
• Mentor and grow a high‑performing team of data scientists and risk analysts.
• Collaborate with Engineering, Product and Finance to translate analytics into business outcomes.

Required profile

• 10+ years of experience in data science, machine learning and consumer credit risk, preferably in fintech or digital lending.
• Proven track record developing and managing credit policies and portfolios at scale.
• Hands‑on experience building, deploying and monitoring production ML models in real‑time environments.
• Strong statistical and mathematical foundation combined with commercial judgment.
• Experience leading technical teams while staying actively involved in model development.

Required skills

• SQL
• Cloud‑based data platforms
• GCP BigQuery (useful but not mandatory)
• MLflow or similar MLOps frameworks

What we offer

• Competitive compensation and equity participation.
• Leadership opportunity to build a data science and credit risk function from the ground up.
• Professional growth in a fast‑moving, mission‑driven fintech.
• Modern machine‑learning stack and cloud infrastructure.
• International scope with impact across multiple markets.