Applied ML Scientist - Fraud & Identity AI (Remote)

SentiLink; Seattle (WA); On-site; USD 180,000 - 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 in-person events

Home office stipend

Job summary

SentiLink is hiring an Applied ML Scientist to build core products that identify fraud and expand risk-related offerings. The role suits new PhD graduates or early-career researchers applying ML to real-world fraud detection, delivering models from research to production at scale.

You will work across teams to research new fraud types, develop products, and provide analyses to drive sales and marketing, with a fast-moving environment and end-to-end ownership.

Qualifications

• PhD/masters/BS with strong quantitative background and research experience
• Strong foundation in ML, statistics, or applied data science
• Experience with Python and data science tools through coursework/research
• Ability to analyze complex problems and build data-driven solutions
• Strong communication skills to explain technical ideas clearly
• Interest in fraud, identity, and financial risk systems

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
• Produce production-ready code for real-time decision making
• Design and present analyses to inform data acquisition and product priorities
• Collaborate with engineering and risk teams to access data and ensure quality

Skills

Machine learning

Data analysis

Python

Communication

Problem solving

Education

Bachelor's/Master's/PhD in quantitative field

Tools

Python

PostgreSQL

AWS

Job description

SentiLink is hiring an Applied ML Scientist to build core products that identify fraud and expand risk-related offerings. The role suits new PhD graduates or early-career researchers applying ML to real-world fraud detection, delivering models from research to production at scale.

You will work across teams to research new fraud types, develop products, and provide analyses to drive sales and marketing, with a fast-moving environment and end-to-end ownership.