Data Science Intern Job at W. R. Berkley Corporation, Chesterfield, MO

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  • W. R. Berkley Corporation
  • Chesterfield, MO

Job Description

 

Midwest Employers Casualty (MEC) is a member of the W. R. Berkley Corporation, a fortune 500 company, rated A+ (Superior) by A.M. Best Company, based in Chesterfield, MO. We improve the quality of life for employees severely injured on the job and help companies understand and mitigate their risk for workers’ compensation injuries. MEC has a friendly, results-focused work environment. We seek employees who take initiative, are quick to adapt, are dependable, and like working as part of a team.

 

Company URL:

 

The company is an equal opportunity employer.

 

The Data Science Intern role offers students pursuing an undergraduate or graduate degree in Data Science, Statistics, Mathematics, or related fields an opportunity to gain hands-on experience in a professional data science environment. This role will provide exposure across many facets of a full stack data scientist including data management, advanced modeling, analytics, visualization, and communication of insights. Interns will work with large data sets to uncover actionable business insights. This position will connect disparate data sources and analyze information to solve business problems. In addition to developing core data analysis skills, interns will learn about IT systems, project management approaches, software development lifecycles, and learn about the insurance industry. We help companies understand and mitigate their risk for workers compensation injuries and get employees who are severely injured on the job the care they need.

 

The Predictive Analytics department explores, arranges, and investigates data to develop valuable analytical processes. MEC has a friendly, results-focused work environment. We seek employees who take the initiative, are quick to adapt, dependable, and like working as part of a team. Our ideal candidate is someone who isn’t afraid to try something new, wants exposure to code management, report automation, documentation, and requirement gathering. This internship enables students to expand their knowledge, skills, and professional network.

 

Key functions include but are not limited to:

Data Management

  • Ensure that data and/or associated reports are accurate and securely delivered in a timely fashion.
  • Identify, research, analyze, and document data errors for correction.
  • Utilize data to answer assigned business problems. Provide written, graphical, and verbal summaries of the analysis.
  • Connect unrelated data sets from multiple sources both inside and outside the organization and extract meaningful insights.
  • Service the data needs of both internal and external customers by providing reports and/or electronic files, as needed.
  • Participate in code review and test code results by analyzing data output.

Exposure

  • Work in a professional environment and interact/network with staff and leadership.
  • Observe and participate in all facets of the model/application development lifecycle including planning, requirements, development, and testing.
  • Develop a basic understanding of information technology especially as it relates to data, data warehousing, ETL processes, and data mining.
  • Understand project management practices and approaches including waterfall and Agile methodologies.

Tools

  • Expected to use and be competent with Microsoft technologies such as SQL Server, Power BI, & the Office Suite.
  • Expected to use and be competent with other applications such as Python, GitHub, Jira, & Confluence.

 

  • Applications should be working toward an undergraduate or master’s degree with a focus in Data Science, Statistics, Mathematics, or related fields.
  • Clearly demonstrates and models WR Berkley and Midwest innovation behaviors.
  • Highly self-motivated and self-directed.
  • Passion for working with data to solve problems.
  • Proficiency with Excel; experience with database querying a plus.
  • Strong analytical and critical thinking skills.
  • Ability to communicate data insights verbally and visually.
  • Proficiency in offering and actively engaging with constructive feedback.

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