Senior Credit Risk ML Scientist

Clair; New York (NY); Hybrid; USD 190,000 - 200,000; Full time

Benefits offered by this job

Medical, Dental, & Vision Coverage

Fully-paid parental leave

Company-sponsored 401k, HSA, and FSA

Unlimited vacation for salaried roles

Work from home setup allowance

Access to your earnings every day onCl

Disability insurance

Job summary

Clair, a fintech employer in New York, seeks an Applied Data Scientist to develop and maintain credit models powering underwriting and decision systems. You will design predictive features from transaction data, forecast income flows, spending, and repayment behaviors, and collaborate with engineering to deploy models in production.

The role blends risk modeling with feature engineering, deploying production-ready ML models, and communicating insights to stakeholders across product and risk

Qualifications

• 5+ years of professional experience in data science and machine learning.
• Experience building and productionizing credit or risk assessment models.
• Strong proficiency in Python and familiarity with modern ML libraries (TensorFlow, PyTorch, XGBoost, etc.).
• Strong command of SQL and experience working with large transactional and time-series datasets.
• Strong communication skills and ability to translate complex findings into actionable insights.
• Experience working with cross-functional teams in a fast-paced production environment.

Responsibilities

• Develop and maintain credit risk and repayment models that directly power Clair’s underwriting and decision systems.
• Design and engineer predictive features using transaction-level data, including the prediction of user income flows, spending, and repayment behaviors.
• Collaborate with engineering teams to deploy, monitor, and optimize models in production environments using AWS and Snowflake ML Platform.
• Build prototypes of new modeling methodologies and present them to stakeholders for evaluation and feedback.
• Investigate and analyze credit performance, identifying root causes of model drift or unexpected repayment behavior.
• Partner cross-functionally with product, risk, and engineering teams to turn data insights into product improvements and credit strategy refinements.
• Communicate technical concepts clearly to both technical and non-technical audiences.
• Stay current on best practices and emerging techniques in credit modeling, explainable AI, and financial ML systems.

Skills

Python

SQL

Machine learning

Communication

Cross-functional collaboration

Tools

TensorFlow

PyTorch

XGBoost

AWS

Snowflake ML Platform

Job description

Clair, a fintech employer in New York, seeks an Applied Data Scientist to develop and maintain credit models powering underwriting and decision systems. You will design predictive features from transaction data, forecast income flows, spending, and repayment behaviors, and collaborate with engineering to deploy models in production.

The role blends risk modeling with feature engineering, deploying production-ready ML models, and communicating insights to stakeholders across product and risk