Head of Data Science & Credit Risk

Role overview

This is a senior leadership opportunity for a Head of Data Science & Credit Risk based in Germany. The role sits at the intersection of machine learning, credit risk, and financial inclusion, with responsibility for shaping and scaling the core decisioning systems that support lending across several Southeast Asian markets.

You will own the full credit intelligence roadmap, spanning model design, deployment, portfolio performance, and business impact. The position involves leading a cross-functional team of data scientists and risk analysts to develop ML-powered underwriting systems that support growth while maintaining disciplined risk management. You will also act as a strategic advisor to senior leadership on credit policy, risk appetite, and market expansion.

The organization operates in a fast-moving, metrics-led, and mission-focused environment where experimentation, scale, and practical impact matter. This is a chance to build data science and credit risk capabilities from the ground up in a rapidly growing fintech business.

Key accountabilities

• Set and drive the overall data science and credit risk agenda, including underwriting models, portfolio risk frameworks, and decisioning architecture.
• Create and launch advanced machine learning solutions for credit scoring, fraud detection, customer segmentation, and customer value optimization.
• Develop real-time and near-real-time decision pipelines that enable scalable underwriting across multiple markets.
• Refine credit policy, approval logic, and risk thresholds to support both growth targets and portfolio quality.
• Put in place MLOps practices for model rollout, monitoring, version control, and live performance measurement.
• Lead portfolio analytics work such as stress testing, expected credit loss analysis, and early warning systems for portfolio deterioration.
• Work closely with finance, product, and operations to improve unit economics, provisioning approaches, and capital allocation decisions.
• Convert complex analytical findings into clear recommendations for executive and board-level discussions.
• Promote a strong experimentation culture through A/B testing and data-informed product improvements.
• Expand and manage partnerships with external data suppliers, credit bureaus, and alternative data ecosystems.
• Recruit, coach, and grow a high-performing team of data scientists and risk analysts.

Requirements

• At least 10 years of experience in data science, machine learning, and consumer credit risk, ideally within fintech, digital lending, BNPL, or earned wage access settings.
• A solid history of building, deploying, and maintaining production ML models in real-time or near-real-time decision systems.
• Strong background in credit portfolio management and the design of credit policies in single-market or multi-market environments.
• Deep command of statistical modeling, machine learning methods, and large-scale data analysis.
• Advanced SQL skills and practical experience with cloud-based data platforms such as GCP, BigQuery, or similar tools.
• Proven leadership in building and scaling technical teams while staying hands-on with the work.
• Ability to explain sophisticated technical and analytical ideas clearly to business leaders and executives.
• Good understanding of experimentation methods such as A/B testing and causal inference.
• Relevant exposure to fintech risk, underwriting systems, or lending products with measurable business impact.
• Knowledge of Southeast Asian credit markets, alternative data sources, or applicable regulatory frameworks is a strong advantage.
• Experience with MLOps tools such as MLflow or comparable platforms is highly desirable.

Benefits

• A competitive compensation package aligned with experience and market benchmarks.
• Equity participation in a high-growth fintech scale-up.
• The chance to build credit risk and machine learning capabilities from an early stage.
• A high-impact role that directly supports financial inclusion in emerging markets.
• A fast-paced environment with strong ownership, autonomy, and mission alignment.
• Access to a modern ML stack and cloud-native infrastructure.
• Clear opportunities for career growth in a rapidly expanding company.
• A culture that values experimentation, innovation, and evidence-based decisions.

Additional information

This role is being presented on behalf of a partner company, which handles applications and all subsequent hiring steps. The partner uses an AI-supported matching process to review applications quickly and fairly against the role’s core requirements before sharing a shortlist with the hiring company. The hiring company’s internal team manages interviews, assessments, and the final decision.

Data privacy notice

By applying, you agree that your personal data may be processed to assess your candidacy and shared with the hiring employer as part of recruitment and pre-contractual steps under applicable data protection laws, including GDPR. You may exercise your rights, including access, correction, deletion, and objection, at any time.

Artificial intelligence tools may be used to support parts of the recruitment process, such as reviewing applications, checking resumes, assessing responses, or flagging inconsistencies based on the information provided. These tools assist the recruitment team but do not replace human judgment, and final hiring decisions are made by people. If you want more information about data handling, you can contact the hiring team.