Senior/Staff Credit Data Scientist

Splash Financial

. Develop and deploy statistical and machine learning models to predict credit risk, delinquency, defaults, and loan losses .

Posted 11/2/2026full-timeRemote • United StatesSenior💰 $143,000 - $220,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and deploying statistical and machine learning models for credit risk analysis, with a strong focus on Python programming and advanced quantitative methodologies. Proven ability to collaborate across teams to translate complex financial data into actionable insights and recommendations.

Highest-signal resume keywords

Python ProgrammingStatistical ModelingCredit Risk AnalyticsPredictive ModelingFeature Engineering

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Statistical ModelingPredictive ModelingRegression AnalysisFeature EngineeringModel ValidationPerformance EvaluationData AnalysisQuantitative Pricing ModelsAI-Powered Agents DevelopmentData Governance

Soft Skills

Strong CommunicationCollaborationMentoringAnalytical ThinkingProblem Solving

Tools & Technologies

Data Science ToolsAnalytical PipelinesMachine Learning ModelsCredit Bureau DataLoan Performance Data

Industry Keywords

Consumer LendingCredit RiskLoan LossesUnderwritingRisk Segmentation

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

Develop and deploy statistical and machine learning models to predict credit risk, delinquency, defaults, and loan losses
Analyze credit bureau, alternative, and loan performance data to improve underwriting, risk segmentation, and credit decisioning
Build quantitative pricing models optimizing risk-adjusted returns, loan performance, and conversion
Develop and evaluate AI-powered agents and workflows for underwriting, pricing, and analytical operations
Apply advanced statistical methods, feature engineering, and model validation techniques
Partner with Engineering to deploy scalable, production-ready models and analytical pipelines using Python and other data science tools
Monitor model performance, investigate data anomalies, and implement improvements based on portfolio trends and realized outcomes
Document modeling methodologies and incorporate model governance, fair lending, data privacy, and responsible AI considerations
Lead complex data science initiatives, mentor colleagues, and provide feedback on analytical approaches and technical implementations
Collaborate with Credit Risk, Product, Engineering, and Finance to translate business challenges into actionable insights and measurable outcomes

Requirements

What you’ll need

Bachelor's degree or foreign equivalent in Statistics, Mathematics, Economics, Computer Science, Data Science, Engineering, or a closely related quantitative field
Minimum of 8 years of progressively responsible professional experience in credit risk analytics, pricing analytics, statistical modeling, or related quantitative functions within consumer lending
Advanced proficiency in Python
Expertise in regression analysis, predictive modeling, feature engineering, model validation, and performance evaluation
Strong understanding of consumer lending credit risk and pricing methodologies
Ability to apply advanced quantitative methodologies to complex financial datasets
Ability to interpret analytical findings and develop data-driven recommendations
Strong communication and collaboration skills
Master's degree or PhD in a related discipline is strongly preferred

Benefits

Comp & perks

Fully remote work freedom (for most roles)
Competitive salary packages
Flexible PTO + 9 company holidays
Equity: Share in our start-up success
Comprehensive and affordable insurance benefits
Paid parental leave for both caregivers
Essential modern equipment to get the job done
Fully paid Claude subscription to supercharge your work
401(k) for your future savings
Quarterly meet-ups: In person & virtual fun
Awesome Splash swag to flaunt your team spirit
Bonus component tied to individual and company performance may be available