Data Scientist II

LexisNexis Risk Solutions • Minneapolis, MN

12h

About The Position

A Data Scientist II should have a basic understanding of best-practice and can execute the methods for projects with supervision. Individuals in this role will continue to provide support to the Data Scientist team members and also begin to lead some analytic efforts.

Requirements

• Master’s degree in statistics, data science, mathematics or quantitative methods.
• Experience with big data technologies and applying large scale machine learning techniques.
• Experience with version control through GitHub.
• Experience with Unix/Linux system architecture and command line tools.
• Experience in credit or fraud risk management industry.
• At least one year of experience building predictive models using machine learning and conducting data analysis using Python, R, SQL or similar software packages.
• At least one year of experience with mainstream programming languages, such as Python, R, Java, 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 and 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.

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.
• Provide support to other data scientists across the organization.
• Critical reviews of data experiments to ensure accuracy, completeness, and feasibility.
• Other duties as assigned.

Benefits

• This job is eligible for an annual incentive bonus.
• We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees