[Remote] Senior Data Scientist - Full Stack at SentiLink

Austin, Texas, United States

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Not SpecifiedCompensation

N/AExperience Level

N/AJob Type

Not SpecifiedVisa

N/AIndustries

Requirements

4+ years relevant work experience & relevant PhD or 6+ 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 “end to end” 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

Responsibilities

Develop and maintain SentiLink’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
Research new types of fraud and develop new SentiLink products around identity verification
Build foundational modeling to drive SentiLink’s expanding suite of Fraud and Financial Risk products
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

Skills

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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