Senior Data Scientist

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.
• 3+ 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.