Data science has grown substantially over the last several years. Analytics has evolved from its early days within underwriting and pricing, and insurance companies have found new opportunities to expand its capabilities. With this momentum, data science teams have grown rapidly as well. In this highly competitive profession, knowing how to optimize and leverage talent is a key factor in the success of the company.

Executive Summary

The long-tailed nature of insurance means that when a policy is written, the cost may not be known for years or even decades. Add to that the constraints due to the regulatory environment, and the combination presents a challenge to leaders seeking to build a high-performing data science team so they can leverage analytics. Leaders need to recruit talent that is independent, innovative and driven by curiosity, says The Hartford's head of Small Commercial and Specialty Data Science. He also notes that building a team with diverse backgrounds will help catalyze different viewpoints to stimulate innovation and growth.

One of the most challenging aspects of insurance is its long-tailed nature. When a policy is written, the cost may not be known for years or even decades, adding additional complexity to the analytics. There are also constraints due to the regulatory environment. The first big piece of attracting and recruiting talent in this hypercompetitive field is to demonstrate the opportunity created by these business problems. These challenges require leaders to recruit talent that is independent, innovative and driven by curiosity.

Understanding the business problem is at the root of success, and that is why The Hartford aligns its data science teams closely with the business. When we hire talent, one of the first training opportunities involves them visiting a field office or shadowing a business team. Data scientists who do not know how the business operates—from selling insurance to servicing a policy and paying a claim—cannot identify with the problem and will be hard-pressed to design the appropriate solution.

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