Sr. Product Data Scientist

Sr. Product Data Scientist (ThreatMetrix, Inc.)

LexisNexis Risk Solutions is a world-leading technology and data analytics company focused on some of the world’s most interesting and challenging problems, including stopping cybercriminals while reducing friction for legitimate consumers. The Product Data Scientist will own the responsibility for ideating, researching, data gathering, modeling, and assist with productionizing new features.

As a Sr. Product Data Scientist, you will play a key role in shaping the future of our digital authentication stack. You will work with engineering labs, analytics teams, professional services and monitor external feedback to create research projects and deliver enhancement/feature guidelines. The ideal candidate will be able to understand in-depth design of features, redesign/enhance those features and work with the rest of the team to develop prototypes as appropriate.

On top of the required technical skills and innovative mindset, the ideal candidate should put a strong emphasis on communicating and collaborating frequently with internal and external teams. It is essential for the candidate to keep a strong business-oriented mind and stay close to the customers’ needs to deliver the most accurate innovations.

Roles and Responsibilities:

• Define, research, prototype, and document guidelines for new products/features
• Work alongside product managers and engineering labs teams to help bring cutting edge enhancement to existing product portfolio
• Work with engineering to gain an in-depth understanding of existing products
• Play an active role in research design
• Build machine learning models on top of derived data from APIs
• Formulate strategy for interpreting data in a real time execution environment
• Work with external vendors for data collection and research purposes
• Interact with customers and professional services teams across regions to understand customer fraud strategy evolution and incorporate that feedback into the product

Requirements:

• Good knowledge and experience building machine learning models
• Good knowledge and experience with data visualization tools, SQL and working with databases, Python/R for data wrangling and analysis in a professional setting
• Familiarity with object-oriented programming languages such as C++, Java, and functional languages such as Rust, and Lisp
• In depth knowledge of fraud prevention and authentication methodologies
• Strong critical thinking and analytical skills. Ability to take an ambiguous problem, use data-informed brainstorming, and articulate product goals and clear metrics
• Ability to integrate with cross-functional business partners worldwide
• Excellent communication skills for addressing technical and non-technical audiences
• Ability to travel as needed