Data Science Intern

Central Insurance CompanyVan Wert, OH

About The Position

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.

Requirements

  • 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

Nice To Haves

  • M.S. Students in Statistics, Mathematics, Economics, Computer Science, Engineering or a similarly related field desired

Responsibilities

  • 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
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