It’s More Than Science: 5 Soft Skills Needed to Become a Data Scientist
Most of the job or educational requirements listed for data scientists are the hard skills: strong mathematics with an emphasis on statistical analysis, computer skills, etc. But a good data scientist (whether you’re hiring one or becoming one) also has a strong set of soft skills. Data science is more than the math and technology; it is also about making that math and technology work for the people who need it. Here are the soft skills every data scientist needs to be effective.
1. The Ability to Understand the Business
Whether the data scientist is working in retail, insurance, energy, or finance, knowledge of the business and industry are essential.
Data analytics is only useful to the extent that it reflects what the business needs, whether the business knows what it needs yet or not. The ability to understand what the business’ strengths and weaknesses are, as well as the ability to focus on where the business has been and where it’s headed, are critical skills for the data scientist to master.
A data scientist need not hold an MBA, but does need to have a firm understanding of what makes this business unique, where it fits within the industry, and what the business needs to remain competitive within that industry’s climate. A data scientist should also be able to recognize trends and leverage trends for the benefit of their company.
2. The Ability to Marry Business Needs With Technical Know-How
The ability to connect where the people and technology intersect is crucial for a data scientist.
Data analysis certainly isn’t new, but the technology used to analyze data is rapidly evolving. New and better ways to do things are always on the horizon. A data scientist needs to be able to take their nose out of the data long enough to evaluate the technologies available to them. They should also be able to recognize which of the available technologies best suits the business plan, whether it be migrating data to the cloud, updating mainframe operations, or adopting new platforms like Hadoop.
3. The Ability to Act as a Translator Between the Tech and Non-Tech Workers
The data scientist literally stands as the middleman between the IT department and the business side of the company. These two sets of people speak different languages. A successful data scientist will be able to hear the production workers and translate this into what technologies can meet their needs. Also, the data scientist needs to be able to hear the IT department’s side of things, and help the production side understand how technology can help, as well as what limits there are on the technologies available.
4. The Ability to Put Data Analytics in Perspective
Sometimes the data tells the company what they want to hear. Other times, it does not. A skilled data scientist will have enough diplomatic (sometimes even political) savvy to present the facts as they are and communicate what this means in a way that everyone understands. Ideally, the data scientist will have solid people skills and will be able to sway the company in the right direction when the data indicates things need to change.
5. A Deep Sense of Curiosity
Unlike many other careers, data science isn’t cut and dried — it calls for innovation and creativity in uncovering new ideas. Data can tell us a lot, but it doesn’t necessarily do so in expected ways. The ability to “think outside the box” and find new solutions to age-old problems makes a great data scientist. Data science is all about discovery and finding answers. Without an innate curiosity driving them, the data scientist can’t make those wonderful discoveries.
Looking for a data scientist? If you find a candidate with these soft skills, they can make the data sing new songs for you. Becoming a data scientist? Hone these skills, and the sky’s the limit for you.