As the field of data science grows in popularity and more organizations realize the power of data, unique careers are emerging
As the inventor Alan Kay once said, “The best way to predict the future is to invent it.” Those with a background in data science—with its mix of mathematics, trend-spotting and analytical skills—are reinventing the future of work, creating new positions and radically expanding how we view old ones.
The requirements for data science and analytics jobs are often multidisciplinary and demand the ability to make intellectual connections between a data scientist’s subject expertise and the data provided. Along with an analytical mindset and tech chops, you also need business acumen, global awareness, critical thinking and relationship skills. The stronger and broader your toolset, the better your career opportunities will be.
Traditional data science jobs that interpret and apply data in order to improve products and processes can be found in every industry, from finance and healthcare to marketing. But here are a few surprising jobs that have popped up in recent times, as organizations discover new and creative ways to use data:
- Disease mapper. Growing urban populations and increased air travel heighten the risk of rapid transmission of contagious diseases. Using available data in smart ways can help society stay ahead of outbreak scenarios. Data can ultimately help doctors proactively move from disease response to more accurate disease prediction. The data scientist’s job here is to build predictive epidemiological models to forecast the spread of infectious diseases. The city of Chicago, for example, has already adopted an algorithmic approach to food safety, sending inspectors to locations that are at a high risk of transmitting foodborne illness.
- Baseball front office analyst. Predictive analytics play a central role in modern baseball, informing everything from player positioning to pitch selection and more. A data analyst’s role is to perform advanced quantitative analysis and predictive modeling to improve team performance. By measuring each player—specifically his batting, pitching and fielding capabilities—teams can focus more accurately on which players to acquire to complement the existing teams’ strengths and weaknesses. It’s no surprise, then, that data science played a pivotal role in helping the Houston Astros win the 2017 World Series.
- Cyber city analyst. Urban areas are highly networked and extremely complex. A cyber city analyst must manage myriad urban data flows to ensure that the systems are reliable and safe. In Kansas City, MO, for instance, government officials rely on “pothole prediction” technology to prevent potholes from developing and requiring street repair. The project uses existing traffic cameras to provide data related to traffic volume and other metrics, such as the age of the pavement. It also considers weather and other anomalies, like traffic accidents or scheduled road maintenance, to anticipate when a section of street will fail.
- Genetic counselor. With ongoing advances in genetic medicine, healthcare providers will increasingly be able to offer customized medicines and treatments to patients. These counselors will use gene-editing tools such as Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) to help patients find the best and most personalized care based on their unique genomes.
- Autonomous transport specialist. Autonomous vehicles of all shapes and sizes are zipping our way, and faster than most people realize. How are all these driverless vehicles going to fit into current transportation systems? Computer-driven cars have a different set of needs than human-driven cars. In this role, a data scientist does a great deal of scenario-building and number-crunching to create proactive processes, propose meaningful insights to improve products and safety, and increase efficiencies.
- Roboticist. Data science has had a major impact in the field of robotics, specifically with the use of machine learning algorithms. A roboticist builds algorithms to help robots acquire new behavioral patterns and the ability to operate semi-autonomously. This has allowed robots to be deployed in more complex fields where they are increasingly used to fill gaps in the supply of manual labor, including in big agriculture where, for example, data science-powered “agrobots” assess the ripeness of a fruit before deciding whether to harvest.
- Investment analyst. With so much money at stake, big data analytics have been widely adopted in the trading world. Algorithmic trading enables computers to make decisions at a more rapid frequency than human beings, allowing an investor to see market trends before his competitors. Analysts own and drive the analytics and insights to develop business and risk intelligence tools and frameworks.
Clearly, data scientists, data engineers and analysts are among the most sought-after positions today. Learning the skills needed to get these in-demand jobs could be the key to launching an incredibly exciting new career. Whichever type of role you pick, the short story is that your work will have a big impact on the future—of business, markets, urban transit, the military, medicine or sports, to name a few.