Senior ML Product ManagerAre you an expert in Machine Learning?Will you like to be part of a dynamic global team?About the BusinessLexisNexis Risk Solutions is the essential partner in the assessment of risk.
Within our Business Services vertical, we offer a multitude of solutions focused on helping businesses of all sizes drive higher revenue growth, maximize operational efficiencies, and improve customer experience.
Our solutions help our customers solve difficult problems in the areas of Anti-Money Laundering/Counter Terrorist Financing, Identity Authentication & Verification, Fraud and Credit Risk mitigation, and Customer Data Management.About the RoleAs a Senior Product Manager, you will be responsible for managing a portfolio of machine learning driven digital identity and device identification products alongside being a product owner of a team of engineers that directly work on delivering innovative functionality and improving existing features.
You will evangelize the value and vision of your areas of focus while promoting a culture of data-driven decision making and risk management with customers and customer-facing teams within our organization.
You will be responsible for advancing our industry-leading digital and device identification products by leading product execution, creating product development plans, managing backlogs, and working closely with a cross-functional team developing and maintaining product ideas that solve customer problems.ResponsibilitiesLeading product execution, development plans, and backlog management.Working closely with cross-functional teams to develop and maintain product ideas that solve customer problems.Identifying opportunities to improve our digital and device identifiers and insights.Driving experimentation, optimization, and measuring outcomes using best practices.Manage go-to-market strategies, ensuring product features and roadmaps are clearly communicated to all stakeholders.RequirementsAt least 5+ years of experience in product management in software.Expertise in Machine Learning.Fraud prevention knowledge preferred but not required.Digital identity or device profiling knowledge preferred but not required.Analytical skills needed to drive insight from billions of data points using tools such as SQL and Snowflake.Demonstrate the ability to solve complex problems with simple solutions.Strong communication and confidence to act as an evangelist for digital and device identification within the business.Track record of communicating complex, technical concepts to a non-technical business audience.Track record of converting non-technical business requirements into technical design documents.Demonstrated ability to manage multiple tasks, projects, and priorities.Strong understanding of software development methodologies like Agile Scrum, Kanban, writing user stories, and some background in software development.Bachelor's or Master's degree in a technical subject is preferred.
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