Applied Scientist, PhD — Real‑Time Fraud & Identity ML (Remote)

SentiLink; San Francisco (CA); Hybrid; USD 120,000 - 220,000; Full time

Benefits offered by this job

Employer paid health insurance

401(k) with employer match

Flexible paid time off

Regular company-wide in-person events

Home office stipend

Job summary

SentiLink is seeking an Applied Scientist to build core ML products that identify fraud and advance financial risk tools. Ideal for new PhD graduates or early-career researchers applying ML to real-world fraud detection, with end-to-end model development and production deployment experience.

The role offers remote work within the U.S. with a preference for in-office collaboration in Austin, San Francisco, or New York. Strong coding and communication skills are required.

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
• 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 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

Machine learning

Python

Statistics

Data analysis

Communication

Education

Bachelor's/Master's/PhD in Statistics, CS, Physics, Mathematics, or related quantitative field

Tools

AWS

PostgreSQL

Job description

SentiLink is seeking an Applied Scientist to build core ML products that identify fraud and advance financial risk tools. Ideal for new PhD graduates or early-career researchers applying ML to real-world fraud detection, with end-to-end model development and production deployment experience.

The role offers remote work within the U.S. with a preference for in-office collaboration in Austin, San Francisco, or New York. Strong coding and communication skills are required.