Data scientist was dubbed the sexiest job of the 21st century a few years ago by the Harvard Business Review, and it continues to live up to its rep. In fact, Bloomberg reports by 2018, the US could face a 50 to 60 percent gap between demand and available analytic talent.
Interested in an IT data scientist career? You're probably wondering, "What are data scientist qualifications?" and "How do I become a data scientist?" For starters, you'll need:
- A deep understanding of applied mathematics and statistics.
- Knowledge of programming languages and applications, such as SQL, R, Python, and Tableau.
- The ability to interpret data and create reports.
- A degree in a discipline like mathematics, statistics, computer science, or economics.
Many schools offer degrees in data science. There are even 12-week immersive boot camps to prepare you for a data scientist career. While quite a few data scientists have earned a master's degree, it's not necessarily a requirement. If you can prove you have the necessary skills, potential clients will pay attention.
Once you are a contract data scientist or have your own data firm, your next hurdle is the liability that comes with your job. Protect yourself from work-related lawsuits with data scientist insurance.
What Risks Can You Expect during a Data Scientist Career?
Data scientists face many of the same risks as other small-business owners or contractors. There's always the chance of property damage or visitor injuries on your property.
But the nature of your work exposes you to some special risks. That's why it is important to have data scientist insurance. It can help out when the following events happen:
- Client slip and trip. A client drops by your office to discuss a new project and trips over a power cord. General Liability Insurance can cover the medical bills for the client's broken arm. If he sues over the injury, it can also pay for your legal fees.
- Late report. An ice storm knocks your power out just as you're trying to finish a client report. You deliver the report two weeks late. Furious, the client sues you for breach of contract. Good thing your Errors & Omissions Insurance can cover legal expenses when you're sued over work mistakes.
- Data breach. When you spend your career digging through data, data breaches are a top liability concerns. If you accidentally expose client data to hackers, it can cost a lot of money to make things right. Most Errors & Omissions policies include Cyber Liability Insurance. It can pay for legal costs when you're sued over a client's breach.
- Employee injury. Your employee trips on the office steps and breaks his leg. Most employers are required to carry Workers' Compensation Insurance to help in these instances. This policy can pay for employee medical expenses and lost wages when they experience a workplace injury.
- Storm damage. A serious windstorm rips through your town. It shatters your office's windows and destroys your computers and printers. A Business Owner's Policy can help pay to replace the broken windows and electronics.
- Employee lawsuit. An employee has been making a lot of mistakes. You've talked to her a few times about her performance and documented each incident. Finally, you decide to let her go. She sues, claiming you wrongfully terminated her employment contract. Your Employment Practices Liability Insurance can help pay for your legal expenses.
- Theft from a client. Clients in the financial services industry often require you to purchase a Fidelity Bond. If one of your employees steals from the client, the bond can cover their loss.
Risk Management Tips for Data Scientists
Even though data scientist requirements primarily include analyzing data and composing reports, that work comes with risk. We can help you figure out which policies make sense for your firm, but we also offer free resources that can help you avoid common business problems.
If you're just getting started, check out this article on how to keep a steady pipeline of clients. This guide can help you figure out when to outsource some nonessential work.