Senior Applied Data Scientist

Role Overview

Join Clair’s Data Science team as a Senior Applied Data Scientist. You will build and maintain credit models and predictive systems that power Clair’s financial products, turning messy real-world data into actionable intelligence.

Key Missions

• Develop and maintain credit risk and repayment models powering Clair’s underwriting and decision systems.
• Design and engineer predictive features using transaction-level data, including:
  • prediction of user income flows
  • spending patterns
  • repayment behaviors.

Responsibilities

• Design new model features.
• Deploy and monitor production-ready ML models.
• Collaborate with cross-functional teams (especially engineering) to deploy, monitor, and optimize models in production.

Requirements

• 5+ years of professional experience in data science and machine learning.
• Strong technical foundation in machine learning and statistical modeling.
• Experience building and productionizing credit/risk assessment models.
• Proven ability to lead end-to-end data science projects (research → model development → deployment & monitoring).
• Strong communication skills to translate complex insights into actionable recommendations.
• Strong command of SQL with large transactional and time-series datasets.
• Proficiency in Python and experience with modern ML libraries (e.g., TensorFlow, PyTorch, XGBoost).
• Experience with cloud ML environments (e.g., AWS, Snowflake ML Platform).
• Experience with time-series analysis and modeling (forecasting, trend detection, temporal feature engineering).
• Familiarity with model explainability and financial compliance requirements.

Nice-to-Haves

• Experience in fintech or credit risk modeling.