Applied ML Scientist

SentiLink provides innovative identity and risk solutions, empowering institutions and individuals to transact with confidence. We’re building the future of identity verification in the United States, replacing a clunky, ineffective, and expensive status quo with solutions that are 10x faster, smarter, and more accurate. Our real-time APIs have helped verify hundreds of millions of identities, starting with financial services and rapidly expanding into new markets. We’re backed by world-class investors including Craft Ventures, Andreessen Horowitz, NYCA, and Max Levchin, and have earned recognition from TechCrunch, CNBC, Bloomberg, Forbes, and others. We’ve been named to the Forbes Fintech 50, won the 2026 FICO Industry Vanguard Decision Award, and were the first company to go live with the eCBSV, even testifying before the United States House of Representatives on the future of identity.

SentiLink supports flexible work arrangements, ranging from fully remote to in-office, with physical offices in Austin, San Francisco, New York City, Seattle, Los Angeles, Chicago, Gurugram (Delhi), and Bengaluru. Some roles are hybrid or in-office by design, such as our engineering team in India, which works primarily from our Gurugram office.

About the role

As an Applied ML Scientist at SentiLink, you will build our core products: models that identify fraudsters and advance our growing suite of financial risk products. This role is ideal for new PhD graduates or early-career researchers interested in applying machine learning to real-world fraud detection. You’ll build and ship machine learning models in a production environment, gaining hands-on experience across the full ML lifecycle—from research and development to deployment at scale. If you want real-world AI and ML exposure in an industry setting, not just research papers, this is the opportunity.

We have open roles on multiple teams, including:

• Emerging Products – focuses on 0-to-1 development of new offerings brought to market
• Application Fraud – analyzes the foundational elements of consumer financial applications to detect all forms of fraud
• Identity – resolves identities across massive, often conflicting data sources (both digital and physical) and generates risk models from limited information

You will be the definitive owner of your domain, working on high-visibility projects that require deep domain understanding, critical thinking, and strong technical abilities. This is a full-stack data science role involving model development, analysis, and writing production code. You should thrive in a fast-moving environment where deep domain expertise drives development and unusual insights create competitive advantage.

This role can be remote within the U.S., with a strong preference for candidates who can work from our Austin, San Francisco, or New York offices.

Technologies

• Python 3
• PostgreSQL
• AWS infrastructure (EC2, S3, RDS, Redshift, etc.)

Responsibilities

• Develop and maintain SentiLink’s fraud detection models through the full model development lifecycle: from data acquisition decisions through featurization, labeling, 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 through iteration, integration of new data sources, and inventive feature engineering.
• Write production-ready code that powers real-time decision-making for our partners.
• Design, perform, and present analyses to inform data acquisition, product development, risk operations, marketing, and sales efforts.
• Collaborate with engineering, risk operations, and data acquisitions teams to access necessary data, maintain data quality, and support data access.

Requirements

• 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.
• 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 varied, high-impact, open-ended problems.

Pay

Salary range: $180,000/year – $220,000/year + equity + benefits. This range is inclusive of multiple career levels, and the actual base salary will be determined by education, experience, skills, and qualifications.

Benefits

• Employer-paid group health insurance for you and your dependents.
• 401(k) plan with employer match (or equivalent for non-U.S.-based roles).
• Flexible paid time off.
• Regular company-wide in-person events.
• Home office stipend, and more.

Corporate Values

• Follow Through
• Deep Understanding
• Whatever It Takes
• Do Something Smart