Senior Data Scientist - Full Stack

Austin, Texas, United States

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Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Financial Services, Identity Verification, FintechIndustries

Requirements

Candidates must possess a relevant PhD with 4+ years of work experience or a relevant Master's degree with 6+ years of experience. A proven track record of solving complex business problems using data science and machine learning solutions is essential, along with experience communicating outcomes to senior management. Strong practical knowledge of machine learning and statistics, including experience with state-of-the-art ML solutions, is required. Proficiency in writing production code and tests, and a willingness to develop deep domain expertise in product-focused work are also necessary.

Responsibilities

The Senior Data Scientist will develop and maintain fraud detection models throughout their lifecycle, including data acquisition, featurization, training, experimentation, productionalization, and monitoring. Responsibilities include researching new fraud types, developing new identity verification products, and building foundational modeling for fraud and financial risk products. The role involves achieving success through iteration, integrating new data sources, and inventive feature engineering, as well as writing production-ready code for real-time decision-making. Additionally, the Senior Data Scientist will design and present analyses to inform various business efforts and collaborate with engineering, risk operations, and data acquisitions teams to ensure data quality and access.

Skills

Data Science

Model Development

Fraud Detection

Financial Risk

Research

Production Code

Critical Thinking

Analysis

SentiLink

Machine learning solutions for identity fraud detection

About SentiLink

SentiLink provides solutions to help financial institutions prevent identity fraud. Their main product uses machine learning models to detect fraudulent activities during the application process. By analyzing data and reviewing cases with a team of risk analysts, SentiLink offers insights that help clients make informed decisions about approving customers. What sets SentiLink apart from competitors is their ability to adapt their products to various types of fraud and customize them to meet the specific needs of each client. The goal of SentiLink is to enable financial institutions to minimize fraud losses while maintaining a positive customer experience.

San Francisco, CaliforniaHeadquarters

2017Year Founded

$81.7MTotal Funding

SERIES_BCompany Stage

Fintech, AI & Machine Learning, Financial ServicesIndustries

51-200Employees

Benefits

Health Insurance

401(k) Retirement Plan

401(k) Company Match

Unlimited Paid Time Off

Home Office Stipend

Risks

Sophisticated fraud techniques may outpace SentiLink's current detection capabilities.

Dependence on high-quality data could impact fraud detection effectiveness if data quality declines.

Intense competition in the fintech sector may threaten SentiLink's market position.

Differentiation

SentiLink specializes in detecting synthetic identities using proprietary machine learning models.

The company offers customizable solutions that integrate seamlessly with clients' existing systems.

SentiLink's Facets tool provides feature-specific intelligence to enhance fraud detection accuracy.

Upsides

Growing demand for synthetic identity fraud detection boosts SentiLink's market potential.

Partnerships with Scienaptic AI and Persona enhance SentiLink's fraud detection capabilities.

API-based solutions allow SentiLink to offer seamless integration and customization.

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