Hybrid Data Scientist III

at RELX

• Job title: Data Scientist III
• Job type: Full Time
• Experience level: Mid level, Senior
• Salary: $78,800 - $131,300 per year
• Degree requirement: Bachelor's Degree
• Tech skills: Java, Python, Scala
• Location requirements: Hybrid, Minneapolis, United States

About the role

• Data Scientist developing predictive models for fraud and credit risk at LexisNexis Risk Solutions. Collaborating with teams to provide statistical analysis and innovative solutions.

Responsibilities

• Understand and execute analytic plans with the appropriate statistical or modeling technique.
• Conduct analyses supporting existing and new product development or customer sales opportunities.
• Assemble, merge and parse large amounts of data to detect meaningful trends and patterns.
• Explore opportunities to enhance existing products with new features or new data sources.
• Develop machine learning models, create model code, and work with internal or external stakeholders to validate accuracy of production code.
• Interpret, document, and communicate analytic work to non-technical audiences.
• Proactively identify and communicate data quality issues and successfully work with other teams to implement solutions.
• Collaborate with cross-functional peers to define product and data science strategies.
• Provide support to other data scientists across the organization.
• Critical reviews of data experiments to ensure accuracy, completeness, and feasibility.

Requirements

• Bachelor’s degree in statistics, data science, mathematics or quantitative methods and at least four years of relevant work experience.
• At least two years of experience building predictive models using machine learning and conducting data analysis using R, Python or similar software packages.
• At least two years of experience with mainstream programming languages, such as Java, R, Python, or Scala, in a collaborative environment using software development best practices such as version control and testing.
• Superior knowledge of data science frameworks, statistical methods and advanced machine learning techniques.
• High degree of creative, analytical and problem-solving skills.
• Ability to learn quickly.
• Ability to work effectively both independently and collaboratively.
• Ability to communicate complex technical or statistical concepts to a non-technical audience.
• Ability to apply modern data exploration and visualization techniques to deliver actionable insights.
• Willingness to adapt to new techniques and an innovative attitude towards finding solutions.
• Fluency with presentation and document programs such as PowerPoint, Word, Excel.

Benefits

• Eligible for an annual incentive bonus