Data Scientist, New Grad

As a Data Scientist at SentiLink, you will build core products: fraud detection models and financial risk models that identify fraudsters and enhance our suite of financial risk offerings. This role is tailored for new PhD graduates or early‑career researchers who want to apply machine learning to real‑world fraud detection. You will build and ship production‑ready models, gaining experience across the full ML lifecycle, from research and development to deployment at scale. The role offers exposure to industry‑level AI and ML challenges beyond academic research.

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.

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 and generates risk models from limited information Technologies

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

Responsibilities Develop and maintain fraud detection models through the full model development lifecycle: data acquisition, featurization, labeling, training, experimentation, productionalization, and monitoring. Build foundational modeling to drive the expansion of SentiLink’s Fraud and Financial Risk products. Research new types of fraud and develop new products around identity verification. Iterate on research, integrate new data sources, and engineer inventive features. Write production‑ready code for real‑time decision making by partners. Design, perform, and present analyses informing data acquisition, product development, risk operations, marketing, and sales. Collaborate with engineering, risk operations, and data acquisition teams to access data, maintain 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 live in the United States. Thrive in a fast‑paced environment characterized by solving extremely varied, high‑impact, open‑ended problems. Salary Range

$120,000/year – $220,000/year + equity + benefits

Note: This salary range is inclusive of multiple career levels, and the actual base salary within that range will be determined by several components including but not limited to the individual's education, experience, skills, and qualifications.

Perks 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! Corporate Values Follow Through Deep Understanding Whatever It Takes Do Something Smart

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