Head Of Data Science & Credit Risk

About the role

The Head of Data Science & Credit Risk will shape the machine‑learning driven underwriting and credit decisioning strategy across fast‑growing markets. Reporting to senior leadership, you will own the full model lifecycle, from development to monitoring, while ensuring responsible lending practices.

Key responsibilities

• Lead design, testing, deployment and continuous improvement of ML models for credit decisioning, fraud detection and risk segmentation.
• Develop underwriting algorithms using alternative data to expand access while managing risk.
• Build and scale real‑time scoring models across multiple products and markets.
• Establish model governance, monitoring, and MLOps practices including versioning and drift detection.
• Define credit risk frameworks, policies, approval strategies and customer segmentation for each market.
• Track portfolio metrics, create early‑warning indicators and conduct stress testing and provisioning.
• Mentor and grow a high‑performing team of data scientists and risk analysts.
• Collaborate with Engineering, Product, Finance and executive stakeholders 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 large‑scale portfolios.
• Hands‑on experience building, deploying and monitoring production ML models in real‑time environments.
• Strong statistical background and ability to run experiments and A/B tests.
• Excellent communication skills to present complex models and risk insights to non‑technical leaders.

Required skills

• SQL
• Cloud‑based data platforms
• GCP BigQuery (optional but useful)
• MLflow or similar MLOps frameworks

What we offer

• Competitive compensation based on experience and location.
• Equity participation in the company.
• Opportunity to build and lead a data science and credit risk function from the ground up.
• Professional growth in a fast‑moving, mission‑driven fintech environment.
• Access to a modern machine‑learning stack and cloud infrastructure.
• International scope with impact across multiple markets.