Senior Credit Data Scientist - Remote & Equity

Splash Financial, Inc.; New York (NY); Remote; USD 143,000 - 220,000; Full time

Benefits offered by this job

Fully remote work freedom

Competitive salary packages

Flexible PTO + 9 company holidays

Equity: Share in our start-up success

Comprehensive benefits

Paid parental leave

Modern equipment

Claude subscription

401(k)

Quarterly meet-ups

Splash swag

Job summary

Splash Financial is seeking a Senior/Staff Credit Data Scientist to advance consumer lending analytics. You will leverage bureau and alternative data to build predictive models, optimize pricing, and drive data-informed lending decisions in a fast-paced, collaborative environment.

The role demands strong technical depth in statistics, modeling, and Python, with a passion for responsible lending and scalable, production-ready solutions.

Qualifications

• 8+ years in credit risk analytics or related quantitative functions.
• Strong Python and data science tooling experience.
• Experience with pricing and risk-based decisioning in consumer lending.

Responsibilities

• Develop and deploy models to predict credit risk, delinquency, defaults, and losses.
• Analyze bureau and alternative data to improve underwriting and pricing.
• Build pricing models to optimize risk-adjusted returns and conversion.
• Collaborate with Engineering to deploy production-quality models and pipelines.
• Monitor model performance and governance, ensuring data privacy and fairness.

Skills

Python

Credit risk analytics

Pricing analytics

Statistical modeling

Data manipulation

Education

Bachelor's degree in a quantitative field

Master's degree or PhD preferred

Tools

Production-grade ML pipelines

Credit bureau data analysis

Job description

Splash Financial is seeking a Senior/Staff Credit Data Scientist to advance consumer lending analytics. You will leverage bureau and alternative data to build predictive models, optimize pricing, and drive data-informed lending decisions in a fast-paced, collaborative environment.

The role demands strong technical depth in statistics, modeling, and Python, with a passion for responsible lending and scalable, production-ready solutions.