Senior Data Scientist, Credit Risk Analytics

Prosper Marketplace

. Build machine learning models for managing credit and fraud risks .

Posted 11/11/2026full-timeRemote • United StatesSenior💰 $129,000 - $179,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and deploying machine learning models for credit and fraud risk management, utilizing statistical programming languages like Python and database languages such as SQL. Strong ability to collaborate across functions while adhering to regulatory guidelines and applying responsible AI techniques.

Highest-signal resume keywords

Machine Learning Model DevelopmentStatistical Programming (Python)Database Languages (SQL)Consumer Lending ExperienceRegulatory Compliance

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningStatistical AnalysisData ExtractionModel MonitoringRisk ManagementPredictive TechniquesData Science Productivity ToolsCoding Best PracticesAd-Hoc AnalysisModel Documentation

Soft Skills

Clear CommunicationCollaborationSelf-MotivationResults OrientationCreativity

Certifications & Qualifications

Advanced Degree (M.S./PhD)

Industry Keywords

FintechCredit RiskFraud RiskConsumer LendingUnsecured Personal LoansCredit CardsRegulatory GuidelinesReproducible ResearchBusiness MetricsData Sources

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

Build machine learning models for managing credit and fraud risks
Leverage complex data sources, including credit bureau reports and customer-supplied information, to develop credit and fraud strategies
Improve credit performance and optimize risk decisions
Collaborate with engineers to deploy models into production
Propose and execute solutions within business constraints
Apply responsible AI techniques in accordance with regulatory requirements and lending best practices
Develop tools and workflow solutions to increase data science productivity
Monitor credit risk models in production
Extract value from data to impact key business metrics
Assess the usefulness and validity of machine learning algorithms and features across data sources
Conduct ad-hoc analysis related to risk management, investor services, operations, and corporate development
Participate in recruiter, department, technical, and team/virtual interviews

Requirements

What you’ll need

3+ years of work experience in fintech, finance, or other high-impact fields applying statistical and machine learning predictive techniques; educational experience taken into consideration
Consumer lending experience in unsecured personal loans or credit cards is a plus
Advanced degree (M.S./PhD), preferably in statistics, computer science, engineering, physical sciences, economics, or a related technical field
Sr. level: M.S. with 6+ years of experience or PhD with 3+ years of experience
Expert knowledge of a statistical programming language such as Python
Expert knowledge of database languages such as SQL
Solid understanding of coding best practices and model documentation
Ability to communicate technical subject matter clearly and succinctly to team members and senior management
Ability to collaborate across functions and develop strong relationships
Ability to work unsupervised in a fast-paced environment and prioritize parallel projects
Ability to work within regulatory guidelines with a mindset toward reproducible research
Self-motivated, results-oriented, enthusiastic, and creative
Qualified non-US citizens may be considered; Prosper will provide green card sponsorship

Benefits

Comp & perks

401(k) with a 5% company match
Flexible time off
Paid parental leave
Annual wellness allowance
Comprehensive health coverage
Udemy access
Childcare assistance
Pet insurance
Additional savings through Beneplace
Flexible work arrangements, including fully remote work or work from San Francisco or Phoenix offices
Bonus