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Salary: USD 190,000 - 200,000 / annual
Clair is a fintech platform on a mission to give America's workers financial freedom by enabling them to access their earnings as soon as they clock out of work. The company embeds its products within scheduling, workforce management, and payroll apps that hourly workers already use daily.
As a Senior Applied Data Scientist, you will develop and maintain the next generation of credit models and predictive systems that power Clair's financial products. You'll shape how millions of hourly workers access affordable credit by leveraging cutting-edge data science to assess risk, predict repayment, and optimize credit decisions.
Key responsibilities include:
- Developing and maintaining credit risk and repayment models that power underwriting and decision systems
- Designing and engineering predictive features using transaction-level data, including prediction of user income flows, spending, and repayment behaviors
- Collaborating with engineering teams to deploy, monitor, and optimize models in production using AWS and Snowflake ML Platform
- Building prototypes of new modeling methodologies and presenting them to stakeholders
- Investigating credit performance and identifying root causes of model drift or unexpected behavior
- Partnering cross-functionally with product, risk, and engineering teams to translate data insights into product improvements
- Communicating technical concepts clearly to both technical and non-technical audiences
- Staying current on best practices in credit modeling, explainable AI, and financial ML systems
You'll need 5+ years of professional data science and machine learning experience with a proven track record of leading end-to-end projects from research through deployment and monitoring. Experience building and productionizing credit or risk assessment models is essential. Strong proficiency in Python, SQL, and modern ML libraries (TensorFlow, PyTorch, XGBoost) is required, along with experience working with large transactional and time-series datasets. Fintech or credit risk modeling experience is preferred, as is familiarity with cloud-based ML environments and model explainability techniques.
This is a hybrid role based in New York City with expectations to come into the office at least three days per week (Tuesdays, Wednesdays, Thursdays), with additional days occasionally for client meetings.
