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SentiLink

Builds software that detects identity fraud

Staff Data Scientist - Full Stack

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeRemote in USA

About the Job

Requirements

  • At least 6 years of relevant work experience and a relevant PhD, or at least 8 years of relevant work experience and a relevant Master's degree.
  • A proven track record of solving complex or high-profile business problems with data science or machine learning solutions.
  • Experience communicating outcomes and progress to senior management or stakeholders.
  • Strong end-to-end data science development experience, including planning, defining success criteria and metrics, obtaining buy-in, and delivering solutions such as production systems, presentations, or strategy documents.
  • Strong practical machine learning and statistics knowledge, including the ability to apply standard tools to scope solutions and investigate them further as needed.
  • Interest in developing deep domain expertise for product-focused work; fraud experience is not required, but willingness to learn is required.
  • Experience writing production code and tests.
  • Must be legally authorized to work in the United States and live in the United States.
  • Ability to thrive in a fast-paced environment involving varied, high-impact, open-ended problems.

Responsibilities

  • Develop and maintain fraud detection models throughout the model development lifecycle, including data acquisition decisions, featurization, focusing labeling resources, model training, experimentation, productionalization, and monitoring.
  • Build foundational modeling for the expanding Fraud and Financial Risk product suite.
  • Research new types of fraud and develop products around identity verification.
  • Research and develop through iteration, integration of new data sources, and inventive feature engineering.
  • Write production-ready code that supports real-time decision-making by partners.
  • Design, perform, and present analyses to inform data acquisition, product development, risk operations priorities, marketing, and sales.
  • Work with engineering, risk operations, and data acquisition teams to access necessary data, maintain data quality, and support data access.

Desired Qualifications

  • Experience with state-of-the-art machine learning solutions is a plus.
  • Familiarity with identity solutions, fintech, or adjacent industries is a bonus.
  • Experience working at a startup is strongly preferred.

About the Company

SentiLink

Builds software that detects identity fraud

SentiLink builds identity verification and fraud detection software for banks, credit unions, lenders and other businesses that need to screen applicants. Its Synthetic Fraud Score checks for invented identities, while ID Theft Score targets applications made with stolen personal information. Customers send applicant data through an API, batch upload or dashboard to receive risk scores and identity signals, and buy access under commercial service agreements. The product suite also includes direct identity checks with the Social Security Administration and tools for investigating suspicious cases. SentiLink was founded in 2017 and is headquartered in San Francisco, California.

Company size
51-200
Company stage
Series B
Total funding
$84M
Headquarters
San Francisco, CA
Founded
2017

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