Fraud Data Scientist, ID.me

• If you are data-driven, results-oriented, and eager to help solve data problems related to fraud, then this would be the perfect opportunity for you
• 2+ years of hands-on experience in fraud analytics or a high-tech mature startup
• 1+ years of experience with deep learning frameworks such as Tensorflow, Tensorflow Recommenders, Pytorch, MXNet, Keras
• MS in a highly quantitative field (Computer Science, Engineering, Math, Operations Research, Physics, Statistics, or related)
• Note that candidates must be located in the continental U.S

Desirable

• We are seeking a Fraud Data Scientist to gather critical insights and identify and analyze fraud patterns across the ID.me network
• In this role, you will work closely with the Fraud Analytics Team, Fraud Investigations Team, Engineering, Product and Customer Success to execute on ID.me’s fraud strategy
• Partner with fraud leadership and fraud investigators to develop our fraud strategy
• Design experiments, test hypotheses, and analyze fraud patterns that are effective at detecting fraud with low false positive rates
• Leverage data analytics evaluate, recommend, and manage fraud strategies to prevent fraudulent activity on the ID.me network
• Respond quickly to fraud attacks by developing fraud monitoring frameworks, dashboards, and solutions in collaboration with cross-functional teams
• Recommend and build automated rules and models to support the detection and prevention of fraudulent activity
• Use signals and data collected by member interactions with the ID.me network to identify the use of stolen Personal Identifiable Information (PII), social engineering, and account takeover (ATO)
• Establish robust monitoring capabilities to ensure high performance of both automated and manual fraud detection processes
• Build strong relationships with key partners and the leadership