Staff Data Scientist — Credit Risk & Fraud Modeling Leader

Earnest; United States; Remote; USD 216,000 - 262,000; Full time

Benefits offered by this job

Health benefits

Dental benefits

Vision benefits

Savings plans

Mac computers

Work-from-home stipend

Internet reimbursement

Phone reimbursement

Employee stock purchase plan

RSUs

401(k) with company match

Tuition reimbursement

Travel perk

Paid time off

Parental leave

Job summary

Earnest is seeking a Staff Data Scientist based in the United States to own risk science systems and influence credit underwriting and fraud models across the business.

You'll lead end-to-end modeling projects, mentor junior data scientists, and collaborate with Risk, Product, Finance, and Engineering to balance growth with risk-adjusted profitability while delivering transparent analytics to senior leadership.

Qualifications

• 8+ years with Python or R and SQL.
• 7+ years in quantitative risk modeling or similar.
• Master's/PhD in a quantitative field.
• Direct ownership of credit underwriting or fraud models in fintech.

Responsibilities

• Own end-to-end risk science systems for credit risk scoring and loss forecasting.
• Lead design, backtesting, and validation of risk models.
• Serve as SME on credit risk modeling and risk-based decisioning engines.
• Lead cross-functional risk modeling projects from conception to production.
• Translate models and findings into narratives for leadership.
• Mentor data scientists and establish modeling governance.
• Align risk strategies with growth, funding and regulatory needs.
• Oversee production-grade risk and fraud pipelines with monitoring.
• Collaborate with MRM for model validation and documentation.

Skills

Python/R

SQL

Risk modeling

Credit risk analytics

Fraud analytics

Machine learning

Model validation

Mentoring

Communication

Education

Master's/PhD in quantitative field

Tools

Looker

Airflow

dbt

Cloud platforms (AWS/GCP/Azure)

Job description

Earnest is seeking a Staff Data Scientist based in the United States to own risk science systems and influence credit underwriting and fraud models across the business.

You'll lead end-to-end modeling projects, mentor junior data scientists, and collaborate with Risk, Product, Finance, and Engineering to balance growth with risk-adjusted profitability while delivering transparent analytics to senior leadership.