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$210,000 – $240,000
Listed on SentiLink’s own careers site. You apply with them directly — we never stand between you and the employer.
What this role is
Lead a team of data scientists building model risk and governance infrastructure for a fraud detection platform used by major US banks. You'll own end-to-end model validation, monitoring, and regulatory compliance while introducing AI tooling to scale the team's work and directly influence how quickly customers adopt new products.
Our summary, not SentiLink’s wording. The full posting is on their site.
Skills this role names
- Amazon Redshift
- Amazon S3
- Amazon Web Services (AWS)
- Git
- MLflow
- Pandas
- PostgreSQL
- Python
- scikit-learn
- SQL
- XGBoost
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What they ask for
Required
- 6+ years applying statistics, ML, or quantitative analytics in industry
- 3+ years managing data science, analytics, or quantitative risk teams
- Background in model risk analytics, quantitative modeling, or large-scale analytics
- Bachelor's degree in Statistics, Math, CS, Economics, Physics, or related quantitative field
- Strong hands-on Python including pipelines, monitoring, and reporting
- Working knowledge of Git and SQL
- Experience with cloud data and compute platforms like S3 and SageMaker or Databricks
- Able to evaluate model performance, calibration, drift, backtesting, and fairness
- Track record of measurable business impact end to end
- Proficient with AI tools: effective prompting, building agent skills, AI-assisted coding
- Sound judgment with sensitive data and clear communication across technical and non-technical audiences
- 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 regulations
- Experience working with model risk teams at banks, fintechs, auditors, or regulators
- Fraud, identity, credit, or financial risk modeling experience
- Experience building or scaling a validation, governance, or analytics function