Data Scientist, New Grad

SentiLink

18h•$120,000 - $220,000•Hybrid

About The Position

SentiLink provides innovative identity and risk solutions, empowering institutions and individuals to transact with confidence. They are building the future of identity verification in the United States, replacing an ineffective status quo with solutions that are 10x faster, smarter, and more accurate. The company has seen tremendous traction, growing quickly, with real-time APIs verifying hundreds of millions of identities, starting in financial services and expanding into new markets. SentiLink is backed by world-class investors and has been recognized by various media outlets, including being named to the Forbes Fintech 50 list every year since 2023. They were also the first company to go live with the eCBSV and testified before the United States House of Representatives on the future of identity. SentiLink supports a variety of work arrangements, from fully remote to in-office, operating as a digital-first company with strong collaboration across the U.S. and India, maintaining physical offices in Austin, San Francisco, New York City, Seattle, Los Angeles, Chicago, Gurugram (Delhi), and Bengaluru. As a Data Scientist at SentiLink, you will be responsible for building core products, specifically models that identify fraudsters and advance the growing suite of financial risk products. This role is designed for new PhD graduates or early-career researchers interested in applying machine learning to real-world fraud detection. You will 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. The position offers real-world AI and ML exposure in an industry setting. Open roles are available on multiple teams, including Emerging Products, Application Fraud, and Identity. You will be technically capable and the definitive owner of your domain, working on high-visibility and high-impact projects requiring deep domain understanding, critical thinking, and strong technical abilities. Collaboration with teams across the company will involve researching new types of fraud, developing new products, and providing analysis to drive sales and marketing. This is a full-stack data science role, encompassing model development, analysis, and writing production code, emphasizing end-to-end ownership and a fast-moving environment where deep domain understanding and unusual insights drive competitive advantage.

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
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