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Intern, Data Science

The Hartford is offering a 2023 Data Science Summer Internship Program designed to prepare you for a challenging and rewarding Data Science career. This competitive 11-week summer program includes a number of unforgettable team building and social events that let you meet and interact with other members of our large analytics community. The Data Science Calendar of Events includes speaker series, leadership panels, modeling competitions and training in insurance and advanced programming/modeling. This program begins in May 2023.

Responsibilities:

  • Build and enhance the predictive power of existing models.
  • Develop state of the art predictive models that help achieve business targets. Partner with product, underwriting, claims, actuarial and other areas to implement predictive models.
  • Evaluate new internal and external data elements and technologies to be included in predictive models.
  • Develop and implement new multivariate methodologies to solve practical business problems.
  • Build databases to facilitate robust analyses.
  • Identify relationships within data sets that can produce meaningful differentiation amongst competitors.
  • Provide insight in to leading analytic practices and produce new and creative analytic solutions.
  • Find patterns and insights in unstructured data.
  • Project management skills to set appropriate timelines.
  • Acquire industry knowledge in order to solve business questions.
  • Potential for machine learning, optimization analysis, simulations research, geospatial statistics and a growing number of advanced analytic topics.

Requirements:

  • Must be authorized to work in the United States without sponsorship now, or in the future.
  • Must be working towards masters degrees or a PhD in quantitative disciplines such as Data Science, Operations Research, Statistics, Business Analytics or other similar degrees.
  • Experience with predictive modeling. 
  • Experience programming with Python or R.
  • Experience with Github.


Equal Opportunity Employer/Females/Minorities/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age