Remote Quantitative Scientist, Fraud & Risk ML (New Grad)

SentiLink; Chicago (IL); On-site; USD 120,000 - 220,000; Full time

Benefits offered by this job

Employer paid health insurance

401(k) match

Flexible PTO

Company events

Job summary

SentiLink is expanding its Quantitative Science team in the United States, building core fraud-detection models and expanding risk products. Ideal candidates are early-career researchers or PhD graduates applying ML to real-world fraud. You will ship production ML, contribute across the ML lifecycle, and work in a fast-paced, collaborative environment.

Remote within the U.S. is possible, with preferences for Austin, San Francisco, or New York offices.

Qualifications

• PhD in Statistics, Computer Science, Physics, Mathematics, or a related quantitative field or equivalent experience/research
• Strong foundation in machine learning, statistics, or applied data science
• Experience with Python and common data science tools
• Demonstrated ability to analyze complex problems and build data-driven solutions
• Strong communication skills and ability to explain technical ideas clearly
• Interest in learning deeply about fraud, identity, and financial risk systems
• Ability to write clean, maintainable code
• Strong attention to detail and curiosity about real-world data problems
• Candidates must be legally authorized to work in the United States and must live in the United States
• Thrive in a fast paced environment characterized by the need to solve extremely varied, high impact, open ended problems

Responsibilities

• Develop and maintain fraud detection models through the full model development lifespan
• Build foundational modeling to drive Fraud and Financial Risk products
• Research new types of fraud and develop new SentiLink products around identity verification
• Achieve success by iterating, integrating new data sources and feature engineering
• Write production-ready code for real-time decision making by partners
• Design and present analyses informing data acquisition, product development, and risk priorities
• Collaborate with engineering, risk operations, and data acquisitions to access data and maintain quality

Skills

Python

Machine learning

Data analysis

Communication

Clean code

Problem solving

Curiosity

Education

PhD in Statistics/CS/Math/Physics

Tools

Python

PostgreSQL

AWS

Job description

SentiLink is expanding its Quantitative Science team in the United States, building core fraud-detection models and expanding risk products. Ideal candidates are early-career researchers or PhD graduates applying ML to real-world fraud. You will ship production ML, contribute across the ML lifecycle, and work in a fast-paced, collaborative environment.

Remote within the U.S. is possible, with preferences for Austin, San Francisco, or New York offices.