Remote Quantitative Scientist — Fraud & Risk ML

SentiLink; New York (NY); On-site; USD 120,000 - 220,000; Full time

Benefits offered by this job

Health insurance

401(k) plan with employer match

Flexible paid time off

Regular company-wide in-person events

Home office stipend

Job summary

SentiLink, a United States-based identity and risk solutions company, seeks a Quantitative Scientist to build fraud detection models and expand risk products. You’ll work across the full ML lifecycle from research to deployment, applying data-driven methods to real-world fraud scenarios in a fast-moving setting.

The role can be remote within the U.S., with a strong preference for candidates near Austin, San Francisco, or New York.

Qualifications

• Bachelor’s, Master’s, or 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 through coursework, research, internships, or personal projects.
• Demonstrated ability to analyze complex problems and build data-driven solutions.
• Strong communication skills and ability to explain technical ideas clearly.

Responsibilities

• Develop and maintain SentiLink’s fraud detection models through the full model development lifespan: from data acquisition decisions through featurization, focusing labeling resources, model training, experimentation, productionalization, and monitoring.
• Build foundational modeling to drive SentiLink’s expanding suite of Fraud and Financial Risk products.
• Research new types of fraud and develop new SentiLink products around identity verification.
• Achieve success by researching / developing through iteration, integration of new data sources and inventive feature engineering.
• Write production-ready code that can be relied on for real-time decision making by our partners.
• Design, perform, and present analyses that will inform data acquisition, product development, risk operations priorities, marketing, and sales efforts.
• Work with engineering, risk operations, and data acquisitions to access necessary data, maintain data quality, and support data access

Skills

Statistics

Machine learning

Data analysis

Python programming

Communication

Problem solving

Quantitative research

Education

Bachelor’s/Master’s/PhD in Statistics, CS, Physics, Mathematics

Tools

PostgreSQL

AWS

EC2

S3

Redshift

Job description

SentiLink, a United States-based identity and risk solutions company, seeks a Quantitative Scientist to build fraud detection models and expand risk products. You’ll work across the full ML lifecycle from research to deployment, applying data-driven methods to real-world fraud scenarios in a fast-moving setting.

The role can be remote within the U.S., with a strong preference for candidates near Austin, San Francisco, or New York.