Credit Risk ML Scientist (Remote)

Prosper Marketplace; United States; Hybrid; USD 129,000 - 179,000; Full time

Benefits offered by this job

401(k) with 5% company match

Flexible time off

Paid parental leave

Wellness allowance

Udemy access

Childcare assistance

Pet insurance

Job summary

Prosper Marketplace is seeking a Data Scientist to develop and deploy predictive models for credit risk and fraud, applying advanced ML techniques to large, diverse data sources. You will collaborate with engineering and risk teams to translate insights into business decisions and strategies.

The role emphasizes production readiness, governance, and impact on credit performance, with opportunities to influence risk strategy and tool development across the organization.

Qualifications

• 2–3+ years applying statistical and ML techniques in fintech or finance.
• Advanced degree (MS/Ph.D.) in statistics, CS, engineering, economics, or related field.
• Expert knowledge of Python and SQL.
• Strong communication and ability to translate technical topics for cross‑functional partners.

Responsibilities

• Build industry‑leading ML models for credit and fraud risk and deploy with engineering.
• Leverage diverse data sources to improve credit performance and risk decisions.
• Propose strategic risk solutions aligned with company objectives.
• Monitor models in production and extract actionable insights to impact key metrics.
• Develop internal tools to improve data science productivity and workflow.

Skills

Machine learning

Python

SQL

Fintech experience

Communication

Education

MS/PhD in statistics or related field

Job description

Prosper Marketplace is seeking a Data Scientist to develop and deploy predictive models for credit risk and fraud, applying advanced ML techniques to large, diverse data sources. You will collaborate with engineering and risk teams to translate insights into business decisions and strategies.

The role emphasizes production readiness, governance, and impact on credit performance, with opportunities to influence risk strategy and tool development across the organization.