Head of Fraud & Risk Data Science
SardineFull Time
Senior (5 to 8 years)
Location Type: Remote Employment Type: Full-Time
SentiLink provides innovative identity and risk solutions, empowering institutions and individuals to transact confidently with one another. By building the future of identity verification in the United States and reinventing the currently clunky, ineffective, and expensive process, 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. In 2021, we 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 have been named to the Forbes Fintech 50 list consecutively since 2023. Last but not least, we’ve even been a part of history -- we were the first company to go public with the eCBSV and testified before the United States House of Representatives.
As a Data Science Manager at SentiLink, you will directly manage a team of talented data scientists that build our suite of products: models that identify fraudsters and also advance our growing suite of products in financial risk. In this capacity, you will be relied upon to be a technical leader, mentor, and owner of your respective domain, both for your own team and the organization. Utilize your abilities as a strong data scientist to mentor your team, probe their understanding and challenge them to do their best work. Your team will often work on projects with high visibility and impact that require deep domain understanding, critical thinking and strong technical abilities. This role requires managing full-stack data scientists, whose work involves model development, analysis, and writing production code. You yourself should share that same skillset and be interested in having end-to-end ownership in 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.
Machine learning solutions for identity fraud detection
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.