SentiLink Corporation logo

Data Science Manager

Job Overview

Location

United States

Job Type

Full-time

Category

Data Science

Date Posted

April 9, 2026

Full Job Description

đź“‹ Description

  • • As a Data Science Manager at SentiLink, you will lead and mentor a team of data scientists building fraud detection and financial risk models, directly impacting the company’s mission to revolutionize identity verification with faster, smarter, and more accurate solutions.
  • • You will manage a growing team of 2-3 data scientists, scaling to 5-6, while providing technical mentorship, driving end-to-end model development from data acquisition to production, and collaborating with product, engineering, and leadership to align on aggressive timelines and business goals.
  • • SentiLink is a high-growth fintech company backed by top-tier investors, recognized in the Forbes Fintech 50 since 2023, and trusted by financial institutions to verify hundreds of millions of identities through real-time APIs, with offices across the U.S. and India supporting a digital-first, collaborative culture.
  • • You will deepen your expertise in fraud detection and identity solutions, sharpen your leadership and communication skills, and gain end-to-end ownership of high-impact projects that shape product strategy, risk operations, and market expansion in a fast-paced, innovation-driven environment.

Skills & Technologies

Python
Go
PostgreSQL
AWS
Remote
$210k-260k
Degree Required

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SentiLink Corporation logo
SentiLink Corporation
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About SentiLink Corporation

SentiLink builds real-time identity verification and fraud prevention infrastructure for banks, fintechs, and government agencies. Its API-driven platform uses machine learning and authoritative data sources to spot synthetic identities, stolen identities, and other high-risk applications at account opening. The company also offers compliance tools for KYC, CIP, and CDD mandates. Headquartered in San Francisco and founded in 2017, SentiLink serves major U.S. lenders and card issuers, reducing fraud losses and manual review costs while improving onboarding speed and accuracy.

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