Lead Data Scientist – Founding Team (FinTech, AI Monitoring Platform)

One of our clients, an early-stage fintech startup, is looking to hire a Senior Data Scientist to join their founding engineering team.

The company is developing an AI-powered monitoring platform that helps financial institutions such as banks, credit card companies, and insurers ensure that their AI/ML-driven decision-making processes remain stable, explainable, and reliable over time.

Their technology leverages representation learning, anomaly detection, and drift detection to identify inconsistencies in financial decision-making before they affect customers or cause regulatory issues.

As the first Senior Data Scientist on the team, you will have a direct impact on the company’s technological direction. You’ll work closely with the founders, influence core algorithmic and scientific choices, and define the AI/ML monitoring strategy from the ground up. This is a unique opportunity to shape both the product and the company’s future.

What You’ll Do

• Design and implement advanced algorithms in representation learning, drift detection, anomaly detection, and model monitoring.
• Apply techniques such as outlier detection, population stability index (PSI), KL divergence, statistical tests, and embeddings to ensure model robustness.
• Analyze complex financial datasets from multiple sources (transactions, risk, credit, insurance).
• Deliver robust, production-grade ML solutions that power the core platform, with a strong focus on fraud detection, credit scoring, and risk modeling.
• Define scientific methodologies and standards for future AI/ML work, including explainability (XAI) and regulatory compliance.
• Collaborate with engineers to bring research models into scalable production systems (MLOps, AWS, Spark, SQL).

Requirements

• M.Sc. in Computer Science, Statistics, Applied Mathematics, or a related discipline (Ph.D. a plus).
• Proven experience in applied Machine Learning, anomaly detection, and drift analysis.
• Strong coding skills in Python and familiarity with ML frameworks such as PyTorch or TensorFlow.
• Experience with model monitoring frameworks (e.g., EvidentlyAI, Deepchecks, River, Alibi Detect) – a strong advantage.
• Background in financial services, fraud detection, risk modeling, or credit/insurance analytics preferred.
• Ability to thrive in a fast-paced, early-stage startup environment and to serve as the first Data Scientist shaping strategy and infrastructure.