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Product Data Decision Science Intern

Dublin, OH โ€ข On-site

Central Mutual Insurance Company
Insurance Servicesย โ€ขย 501 - 1,000 employees

Internship

Posted 12 days ago


Key responsibilities

  • Apply statistical and analytics techniques to complete a project from start to finish.

  • Generate and validate SQL queries to gather data for hypothesis testing.

  • Perform exploratory data analysis to identify patterns and support discovery.


Job description

At Central, we believe an internship should be more than completing busy work. We invest in our interns to give them the opportunities needed to grow, nurture and develop their whole self. Why? Because we believe excellence is gained from experience.
Central's internship program is customized to each internship placement. The program provides members with dedicated time to gain first-hand experience while solving unique business problems. It's strategically designed to provide diverse exposures throughout the organization, to allow you to learn from our experts and collaborate with teams that do incredible work.
Each internship will be different; however, at its core, the program consists of the following opportunities:
  • Immersive experiences in challenging and meaningful work with built-in continuous learning opportunities
  • Direct impact on work that matters and opportunities to affect successful outcomes and drive corporate objectives
  • Gain the skills and knowledge to become a future trailblazer
  • Build a lasting professional network through events and activities

Data Scientist Internship
  • Apply statistical and analytics techniques to charter a project from start to finish
  • Generate and validate SQL queries to pull together disparate data for hypothesis testing
  • Perform exploratory data analysis to unlock patterns and promote discovery
  • Move from EDA to modeling with the capability to generate predictions
  • Leverage best practices in data visualization to communicate findings and distribute learnings throughout the organization through data story-telling

Ready to dive in? Ideal candidates for this program are:
  • Naturally curious and ask a lot of questions
  • Interest in learning the ins-and-outs of the insurance industry
  • Capable of coding in either R or Python
  • Knowledge and experience building standard predictive modeling techniques including: linear and non-linear models, regression analyses, machine learning methods (decision trees, XG Boosted trees, neural networks, cluster analysis (KNN), feature selection, etc.), forecasting, time series analysis, survival analysis, and causal impact analyses
  • Capable of writing SQL queries to generate datasets
  • M.S. Students in Statistics, Mathematics, Economics, Computer Science, Engineering or a similarly related field desired

Next Steps
  • Applications Accepted: Through January 2027, or until all positions are filled
  • Interviews & Offers: Conducted and extended on a rolling basis
  • Internship Dates: May-August 2027, aligning with summer break

Candidates are encouraged to apply early. The job posting will close once all internship positions have been filled.
Work Authorization
Central will only employ those who are legally authorized to work in the United States. This is not a position for which sponsorship will be provided. Individuals with temporary visas such as E, F-1(including those with OPT or CPT) , H-1, H-2, L-1, B, J or TN, or who need sponsorship for work authorization now or in the future, are not eligible for hire.
Equal Opportunity Employer
It is the policy of Central that all recruiting, hiring, training, compensation, overtime, job classification and assignment, facilities, promotions, transfers, employee treatment and all other terms and conditions of employment shall be maintained in a manner which will not discriminate against any person because of race, color, age, sex, national origin, ancestry, religion, marital status, military status, or disability. The applicant should respond to questions on this application in a way that will not divulge such information.