Data Science Manager, Model Risk

The role

You will lead a team of 3+ data scientists to measure, stress-test, explain, and monitor fraud detection and identity verification models. You will own the model risk strategy, build assurance models, and work with model risk teams at major financial institutions.

What you will do

• Manage a team of 3+ data scientists and set how they work.
• Own strategy and execution for model risk including roadmap and priorities.
• Own technical core including performance monitoring, validation, and bias assessments.
• Build assurance models that audit production models and produce evaluation metrics.
• Move AI from one-off projects to a first-tier tool across the team's work.
• Act as an independent technical counterpart to Applied ML.
• Produce validation reports and documentation for leadership, customers, auditors, and regulators.
• Work with partner model risk teams at major banks and FIs.

Required qualifications

• 6+ years applying statistics, ML, or quantitative analytics in industry.
• 3+ years managing DS, analytics, or quant risk teams.
• Background in at least one of: model or portfolio risk analytics; modeling in a supporting or consulting role; large-scale analytics, reporting, or BI.
• Degree in Statistics, Math, CS, Economics, Physics, or another quantitative field.
• Strong hands-on Python, including building recurring pipelines, monitoring, or reporting.
• Working knowledge of Git and SQL.
• Experience with cloud data and compute like S3 and SageMaker or Databricks.
• Able to read a model and interrogate its methodology: performance evaluation, calibration, drift, backtesting, and fairness.
• Track record of measurable business impact, end to end.
• Proficient with AI tools in daily work: effective prompting, building and using agent skills, and AI-assisted coding and analysis.
• Sound judgment with sensitive data, and clear communication with technical and non-technical audiences.
• Must be legally authorized to work in and reside in the US

Nice to have

• Familiarity with SR 11-7, SR 26-2, OCC guidance, or fair lending.
• Experience working with model risk teams at banks or fintechs, auditors, or regulators.
• Fraud, identity, credit, or financial risk model experience.
• Experience building or scaling a validation, governance, or analytics function.
• AWS preferred

Benefits

• Employer paid group health insurance for you and your dependents
• 401(k) plan with employer match (or equivalent for non US-based roles)
• Flexible paid time off
• Regular company-wide in-person events
• Home office stipend

About the company

SentiLink helps institutions and protects customers by accurately resolving identities and flagging fraud risk. They serve 13 of the top 15 U.S. banks and are a digital-first company with offices in the U.S. and India.