About the role
We are looking for a Senior Data Scientist to build and deploy machine learning models that power fraud detection, risk scoring, and credit decisioning for our fintech and banking partners. You will own the end-to-end model lifecycle, from data exploration and feature engineering to deployment, monitoring, and iteration, while working closely with engineering and product teams.
Responsibilities:
- Develop machine learning and statistical models for fraud prevention, risk scoring, and credit underwriting.
- Analyze large-scale behavioral and transactional datasets to identify patterns, anomalies, and emerging fraud trends.
- Design and run experiments to evaluate, compare, and improve model performance.
- Partner with engineering to deploy models into production and ensure they are reliable, observable, and performant at scale.
- Monitor live models for drift and degradation, and lead retraining and improvement cycles.
- Collaborate with product and risk teams to translate business problems into modeling solutions.
Requirements:
- Bachelor's degree or higher in computer science, statistics, applied mathematics, or a related field.
- 5+ years of experience in data science, with exposure to fintech or financial services preferred.
- Strong expertise in Python and SQL, and hands-on experience with ML frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow.
- Solid foundation in classical machine learning, statistical modeling, and experiment design.
- Experience taking models from notebook to production, including monitoring and iteration.
- Ability to communicate complex findings clearly to technical and non-technical stakeholders.