Chief Data Science & Credit Risk Leader

Jobgether; United States; On-site; USD 180,000 - 260,000; Full time

Benefits offered by this job

Equity program

Leadership opportunity

Modern tech stack

International expansion

Meaningful impact

Mission-driven environment

Job summary

Jobgether's partner company in the United States seeks a Head Of Data Science & Credit Risk to lead ML-powered underwriting and risk decisioning across multiple markets. You will own the full lifecycle of risk models—from development and deployment to monitoring, experimentation, and measurable business impact—and build a high‑performing data science and risk analytics team.

Working with engineering, product, finance, and executives, you will translate advanced analytics into practical decisions

Qualifications

• 10+ years in data science and consumer credit risk.
• Proven leadership of technical teams.
• Experience building production ML for real-time decisions.
• Strong SQL and cloud data platforms knowledge.
• Familiarity with IFRS 9 and regulatory risk.

Responsibilities

• Lead ML model development for credit decisioning, fraud detection, risk segmentation.
• Oversee underwriting innovation with alternative data sources.
• Manage real-time scoring across markets.
• Establish model governance and monitoring.
• Drive MLOps for deployment and lifecycle management.
• Develop credit risk strategies and thresholds.
• Monitor portfolio health and stress testing.
• Lead experimentation and A/B testing.
• Communicate insights to executives and board.

Skills

Data science

Credit risk

Leadership

Production ML

Experimentation

SQL

Cloud platforms

MLOps

Communication

IFRS 9

Regulatory knowledge

Tools

MLflow

Job description

Jobgether's partner company in the United States seeks a Head Of Data Science & Credit Risk to lead ML-powered underwriting and risk decisioning across multiple markets. You will own the full lifecycle of risk models—from development and deployment to monitoring, experimentation, and measurable business impact—and build a high‑performing data science and risk analytics team.

Working with engineering, product, finance, and executives, you will translate advanced analytics into practical decisions