ForMotiv is a real-time web behavioral science company. Our SaaS platform monitors user-behavior in web applications, and makes web-speed recommendations (< 100ms) to improve conversion and reduce fraud. The behavioral data we capture and share with customers is unique, 1st party, and doesn’t contain any PII information. The ForMotiv platform processes over 100 million monthly application journeys and drives value across a variety of use cases for customers ranging from unicorn InsurTechs and FinTechs to Top 10 Insurance and Financial Services firms. You’ll recognize our customer brands.
We’re looking for someone to join our data science team as a data scientist working on our Fraud Solutions. We’re a startup (albeit 6 years old) and this is a hands-on position that bridges the data science, product, and account management teams. We’re actively creating turnkey behavioral data science products, and looking for a data scientist to drive the development of our fraud solutions and uncover fraud trends in customer data. This is a rare opportunity to get in on the ground-floor of a rapidly growing international startup. As our data scientist, you will report to the CDO and work directly with the data science and account management teams.
Our tech stack runs entirely within AWS (and AWS Data experience is required), and leverages serverless, container-based facilities to create a highly performant and highly reliable service-based architecture.
Perks:
The 5 Cultural Characteristics we look for:
About ForMotiv:
ForMotiv is the first Digital Behavioral Intelligence (DBI) platform. Using advanced, explanation-based predictive behavioral analytics, ForMotiv gives organizations unprecedented levels of insight into their users, leading to increased conversions, better digital experiences, and reduced risk and fraud. We’re well financed and have earned the business of some of the world’s most well-respected financial services companies. We’re a scrappy, collaborative group that is open to challenging each other and believe in learning something new everyday.
Job Type: Full-time Remote
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