Data Scientist at Sentilink

SentiLink is building the future of identity verification in the United States. The existing ways to determine if somebody is who they claim to be are too clunky, ineffective, and expensive, but we believe strongly that the future will be 10x better. 

We’ve had tremendous traction and are growing extremely quickly. Already our real-time APIs have helped verify hundreds of millions of identities, beginning with financial services. We’ve recently raised a $70M Series B round, led by Craft Ventures to rapidly scale our best in class products. We’ve earned coverage and awards from TechCrunch, CNBC, Bloomberg, Forbes, Business Insider, PYMNTS, American Banker, LendIt, and others. And we’ve even been a part of history--we were the first company to go live with eCBSV and testified before the United States House of Representatives.

As a Data Scientist at SentiLink, you will build our core products: models that identify fraudsters. 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.

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

This is a remote, US-based role.


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
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:

2+ years relevant work experience and PhD or Master’s in a technical field or 2+ years additional relevant work experience
People who generate creative ideas that provide our competitive advantage
Interest in developing deep domain expertise for product-focused work: a background in fraud is not required, but willingness to learn is
Ability to design, perform, and present thoughtful statistical analysis with business-changing implications
Experience writing production code and tests
Understanding of different machine learning models and their trade-offs
Detail oriented and thoughtful -- someone we can rely on to make business-changing decisions
Ability and desire to take initiative and follow projects through to completion
Bonus for familiarity with: fintech or adjacent industries; identity solutions; distributed computing frameworks; data engineering; AWS
Candidates must be legally authorized to work in the United States and must live in the United States



Perks:

Remote work with home office stipend, and regular company-wide in-person events
Lunch, coffee and snacks during the work day are fully reimbursable
We pay for healthcare for you and your dependents
. . . and other typical start-up benefits (e.g. 401k match, unlimited PTO, etc.)



Corporate Values:

Follow Through
Deep Understanding
Whatever It Takes
Do Something Smart