There aren’t many downsides to a data science career in the insurance industry. Data scientist has been called the “sexiest job of the 21st century” (OK, the Harvard Business Review said it, but it’s still a pretty solid endorsement).
Data science is changing risk management and insurance. At companies of all sizes, data scientists are fundamentally altering the roles of traditional insurance professions like underwriting and claims—and they’re doing it through a lot of challenging, cool projects that require chops in computer science, business, statistics and people skills.
This varied, interesting work requires a wide range of skills. At the top of the list:
- Data analysis
- R (coding language)
- Python (coding language)
- Machine learning
Here’s what it takes to get a data science career.
Undergraduate degree required? Yes, preferably in data science, mathematics, statistics, computer science or engineering.
Advanced degrees required? Usually. Most data scientists have a master’s degree, and many opt to earn a PhD.
Additional requirements? Not usually. However, data science changes fast. Anything you can do to show you’re on the cutting edge of new learning can help distinguish you. Common certifications include Certified Analytics Professional (CAP), Cloudera Certified Professional-Data Scientist (CCP:DS) and EMC Data Scientist Associate (EMCDSA).
Typical career path: Most data scientists start as a junior data scientist or data analyst and earn promotions to mid-level or senior data scientist.
- Entry level: $86,366
- Senior level: $128,011
- Median: $112,000
Entry-level job titles:
- Junior Data Scientist
- Data Analyst