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CI
Central Insurance Company
Data Scientist Intern
Entry-Level JobVerifiedNo experience needed
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Based on Ohio data
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What they do
A Data Scientist utilizes skills and experience to systematically answer questions using data to provide actionable recommendations. Commonly utilizes advanced statistical analysis and machine learning techniques. Common responsibilities also include data cleaning and data management.
$105,235 / year median in Ohio
+16% projected growth
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