Senior Applied Data Scientist

Clair • New York, NY

1d • $190,000 - $200,000 • Hybrid

About The Position

As a Senior Applied Data Scientist on Clair’s Data Science team, you will develop and maintain credit models and predictive systems that power Clair’s financial products. The role focuses on assessing risk, predicting repayment, and optimizing credit decisions for hourly workers. It combines credit modeling and feature engineering, including designing predictive features based on user transaction data and deploying and monitoring production-ready machine learning models.

You will work at the intersection of data science, machine learning, and fintech, translating real-world data into actionable intelligence. Success requires a strong technical foundation in machine learning and statistical modeling, hands-on experience deploying models, and the ability to collaborate and communicate effectively with engineering, product, and risk teams.

This is a hybrid position based in New York City. Employees are expected to work from the office at least three days a week—Tuesdays, Wednesdays, and Thursdays—with additional office days occasionally for client meetings. The annual base salary is $190,000–$200,000; base pay depends on factors including education, skills, and experience. Equity, benefits, and additional perks are also part of the total compensation package.

Requirements

• At least 5 years of professional experience in data science and machine learning.
• A proven track record of leading end-to-end data science projects, from research and model development through deployment and monitoring.
• Experience building and productionizing credit or risk assessment models.
• Strong proficiency in Python and familiarity with modern machine learning libraries such as TensorFlow, PyTorch, and XGBoost.
• 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.

Nice To Haves

• Experience in fintech or credit risk modeling.
• Experience with cloud-based machine learning environments such as AWS, Azure, or Snowflake ML Platform.
• Familiarity with model explainability techniques and compliance requirements in financial modeling.
• Experience with time-series analysis and modeling, including forecasting, trend detection, and temporal feature engineering.

Responsibilities

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

Benefits

• Medical, dental, and vision coverage, with the option to extend coverage to family.
• Fully paid parental leave.
• Company-sponsored 401(k), HSA, and FSA.
• Unlimited vacation for salaried roles and generous PTO for hourly roles.
• Work-from-home setup allowance.
• Access to earnings every day on Clair.
• Company-sponsored short-term and long-term disability insurance.
• Equity and additional perks.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed