Data Scientist, Full Stack

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. SentiLink is backed by world-class investors including Craft Ventures, Andreessen Horowitz, NYCA, and Max Levchin.

About the role

As a Data Scientist at SentiLink, you will build our core products: models that identify fraudsters and advance our growing suite of products in financial risk. This is a full-stack data science role, involving model development, analysis, and writing production code. You should be interested in having end-to-end ownership and a fast-moving environment where deep domain understanding drives development and unusual insights drive our competitive advantage. Technologies include Python 3, PostgreSQL, and 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, 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.

Requirements

• 2+ years relevant work experience & relevant PhD or 4+ years & relevant Masters.
• Proven track record of solving complex/high-profile business problems with DS/ML solutions.
• Experience communicating outcomes/progress to senior management/stakeholders.
• Very strong in “end-to-end” DS development: planning, fleshing out success criteria/metrics, getting buy-in, developing the solution, delivering the solution (prod/deck/strategy doc/etc).
• Strong practical ML/Stats knowledge, i.e., can easily employ the suite of standard ML/stats tools to quickly scope out solutions and double down where needed. Experience with SOTA ML solutions is a plus.
• Interest in developing deep domain expertise for product-focused work: a background in fraud is not required, but willingness to learn is.
• Experience writing production code and tests.
• Detail-oriented and thoughtful—someone we can rely on to make business-changing decisions.
• Experience working at a startup.
• Bonus for familiarity with: identity solutions, fintech, or adjacent industries.
• 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.

Pay

Salary Range: $180,000/year - $220,000/year + equity + benefits

Benefits

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

Schedule

SentiLink supports a variety of ways to work, ranging from fully remote to in-office. We operate as a digital-first company with strong collaboration across the U.S. and India. Some roles are hybrid or in-office by design (e.g., our engineering team in India works primarily from our Gurugram office). If you’re located near one of our offices (Austin, San Francisco, New York City, Seattle, Los Angeles, Chicago, Gurugram, or Bengaluru), we encourage regular in-office time.