Applied ML Scientist – Fraud & Identity Risks (Remote)

SentiLink; New York (NY); Hybrid; USD 180,000 - 220,000; Full time

Benefits offered by this job

Employer paid health insurance

401(k) plan 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 fraudsters and expand financial risk offerings. This 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 gain hands-on experience across the full ML lifecycle, collaborating with teams across the company, and developing end-to-end ownership in a fast-moving environment.

Qualifications

• Quantitative degree or equivalent research in statistics, CS, physics or math.
• Strong foundation in ML, statistics, or applied data science.
• Experience with Python and data science tools.
• Authorized to work in the United States and reside in the United States.

Responsibilities

• Develop and maintain fraud-detection models across the ML lifecycle (research, features, training, productionalization, monitoring).
• Build foundational modeling for SentiLink’s fraud and financial risk products.
• Research new fraud types and develop related products around identity verification.
• Iterate with new data sources and inventive features to drive insights and competitive advantage.
• Write production-ready code for real-time decision making with partners.
• Design and present analyses informing data acquisition, product development, risk priorities, marketing, and sales.
• Collaborate with engineering, risk operations, and data acquisitions to ensure data quality and access.

Skills

Machine learning

Statistics

Python

Data science

Communication

Clean code

Education

Bachelor's/Master's/PhD in Statistics, CS, Physics, Math

Tools

Python

PostgreSQL

AWS

Job description

SentiLink is hiring an Applied ML Scientist to build core products that identify fraudsters and expand financial risk offerings. This 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 gain hands-on experience across the full ML lifecycle, collaborating with teams across the company, and developing end-to-end ownership in a fast-moving environment.