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Staff Applied ML Scientist

๐Ÿ“… Mar 13
Applied Machine LearningData ScienceStatistical AnalysisFraud Detection
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๐Ÿ“œ Description

  • Develop and maintain fraud detection models across the full lifecycle, from data acquisition and feature engineering to training, production, and monitoring.
  • Build models for fraud and financial risk products, including new identity verification offerings.
  • Research emerging fraud patterns and develop products through iteration and integration of new data sources.
  • Write production-ready code and tests for real-time partner decisions.
  • Design and present analyses that inform product development, data acquisition, risk operations, marketing, and sales.
  • Collaborate with engineering, risk operations, and data acquisition teams to access data and maintain data quality.

๐Ÿ› ๏ธ Requirements

  • 6+ years relevant work experience & relevant PhD or 8+ years & relevant Masters
  • Proven track record of solving complex / high profile business problems with DS / ML solutions
  • Experience in communicating outcomes / progress to senior management / stakeholders
  • Very strong in โ€œend to endโ€ DS development: Planning, fleshing out success criteria / metrics, getting buy-in, developing the solution, delivering the solution (prod / deck / strategy doc / etc)
  • 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
  • Bonus for familiarity with: identity solutions, fintech, or adjacent industries
  • Experience working at a startup strongly preferred
  • Thrive in a fast paced environment characterized by the need to solve extremely varied, high impact, open ended problems.

โœจ 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!
Full job description

SentiLink helps institutions and protects customers by accurately resolving identities and flagging fraud risk. Each day, we verify more than 3 million identities, flagging 150k+ fraud attempts in the process. The problems we work on are challenging, and solving them takes deep domain expertise, rigorous analysis, and a willingness to dig into the details.

At SentiLink, you'll work alongside smart, highly collaborative colleagues who respect each other's time and judgment, take ownership, and follow through on their commitments. Together, we do truly meaningful work protecting the identities of innocent consumers and flagging the fraudsters attempting to exploit them.

We're well capitalized and growing quickly. We already serve 13 of the top 15 U.S. banks, we're expanding into new markets, and we're backed by Craft Ventures, Andreessen Horowitz, NYCA, and Max Levchin. We've been named to the Forbes Fintech 50 and as a 2026 FICO Industry Vanguard Decision Award Winner. We were also the first company to go live with the electronic Consent Based Social Security Number Verification (eCBSV) service, and we've testified before the U.S. Congress on the future of identity.

We want SentiLink to be the best place you've ever worked. We offer generous benefits and support a range of working arrangements, from fully remote to in-office. We are a digital-first company with strong collaboration across the U.S. and India, and we meet in person regularly to build relationships. We have offices in Austin, San Francisco, New York City, Seattle (Bellevue), Los Angeles, and Chicago in the U.S., and in Gurugram (Delhi) and Bengaluru in India.

Role:

As a Staff Applied ML Scientist at SentiLink, you will build our core products: models that identify fraudsters and also advance our growing suite of products in financial risk. As an experienced researcher you will be relied upon to be technically capable and the definitive owner of your respective domain. You will often work on projects with high visibility and impact that require deep domain understanding, critical thinking and strong technical abilities. You will work with teams across the company to research new types of fraud, develop new products, and provide analysis to drive sales and marketing. 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 rather than optimization of new machine learning methodologies.

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

Technologies:

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

Responsibilities:

  • Develop and maintain SentiLinkโ€™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 SentiLinkโ€™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:

  • 6+ years relevant work experience & relevant PhD or 8+ years & relevant Masters

  • Proven track record of solving complex / high profile business problems with DS / ML solutions

  • Experience in communicating outcomes / progress to senior management / stakeholders

  • Very strong in โ€œend to endโ€ 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

  • Bonus for familiarity with: identity solutions, fintech, or adjacent industries

  • Experience working at a startup strongly preferred

  • Thrive in a fast paced environment characterized by the need to solve extremely varied, high impact, open ended problems.

  • Candidates must be legally authorized to work in the United States and must live in the United States

Salary Range:

  • $220,000/year - $260,000/year + equity + benefits

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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