Senior Applied Data Scientist

Clair

. Develop and maintain credit risk and repayment models powering Clair’s underwriting and decision systems .

Posted 10/14/2026full-timeNew York City • New York • United StatesSenior💰 $190,000 - $200,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and maintaining credit risk and repayment models, utilizing advanced machine learning techniques and cloud-based environments. Proficient in translating complex data insights into actionable strategies while collaborating effectively with cross-functional teams.

Highest-signal resume keywords

Credit Risk ModelingMachine LearningPython ProgrammingSQL ProficiencyAWS Cloud Services

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ScienceModel DevelopmentPredictive ModelingTime-Series AnalysisFeature EngineeringModel ExplainabilityStatistical AnalysisForecastingRoot Cause AnalysisModel Monitoring

Soft Skills

Strong CommunicationCollaborationStakeholder EngagementProblem SolvingAdaptability

Tools & Technologies

Snowflake ML PlatformTensorFlowPyTorchXGBoostAWSAzure

Industry Keywords

FintechCredit RiskFinancial ModelingCompliance RequirementsData Insights

Tech Stack

Tools & technologies

AWSAzureCloudPythonPyTorchSQLTensorflow

About the role

Key responsibilities & impact

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 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 and analyze credit performance, identifying 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 to technical and non-technical audiences
Stay current on best practices and emerging techniques in credit modeling, explainable AI, and financial ML systems

Requirements

What you’ll need

5+ years of professional experience in data science and machine learning
Proven track record of leading end-to-end data science projects—from research and model development to deployment and monitoring
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
Experience in fintech or credit risk modeling
Experience with cloud-based machine learning environments (AWS, Azure, Snowflake ML Platform, etc.)
Familiarity with model explainability techniques and compliance requirements in financial modeling
Experience working with time-series analysis and modeling, including forecasting, trend detection, and temporal feature engineering
Expected to come into the New York City office at least three days a week

Benefits

Comp & perks

Medical, Dental, & Vision Coverage, with option to extend to your family
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 on Clair
Company-sponsored short-term and long-term disability insurance
Equity
Additional perks