ML Research Scientist (PhD) — Fraud & Identity, Remote

SentiLink; Seattle (WA); On-site; USD 132,000 - 220,000; Full time

Benefits offered by this job

Employer paid group health insurance

401(k) with employer match

Flexible paid time off

Regular company-wide events

Home office stipend

Job summary

SentiLink, a leader in identity and risk solutions, seeks a Research Scientist to build ML models that detect fraud and advance our risk products. You’ll deploy end‑to‑end ML workflows in production, gaining hands‑on experience across the full lifecycle in a fast‑moving team.

Ideal candidates have a PhD or equivalent, strong ML/statistics background, and are proficient in Python and data tooling. Remote within the U.S. is supported, with preference for Austin, SF, or NY offices.

Qualifications

• PhD or equivalent in a quantitative field or research experience.
• Strong foundation in machine learning, statistics, or applied data science.
• Experience with Python and common data science tools through coursework or projects.
• Ability to analyze complex problems and build data-driven solutions.
• Strong communication skills and ability to explain technical ideas clearly.
• Legal authorization to work in the United States.

Responsibilities

• Develop and maintain fraud-detection models across the full ML lifecycle.
• Build foundational modeling for fraud and financial risk products.
• Research new fraud types and develop SentiLink products around identity verification.
• Write production-ready code for real-time decision making.
• Design analyses to inform data acquisition, product development, and risk priorities.
• Collaborate with engineering, risk operations, and data acquisitions teams.

Skills

Machine learning

Python

Statistics

Data analysis

Education

PhD in Statistics/Computer Science/ Mathematics or related

Tools

Python

PostgreSQL

AWS

Job description

SentiLink, a leader in identity and risk solutions, seeks a Research Scientist to build ML models that detect fraud and advance our risk products. You’ll deploy end‑to‑end ML workflows in production, gaining hands‑on experience across the full lifecycle in a fast‑moving team.

Ideal candidates have a PhD or equivalent, strong ML/statistics background, and are proficient in Python and data tooling. Remote within the U.S. is supported, with preference for Austin, SF, or NY offices.