The title “data scientist” has been around for only a few years, but thousands of professionals are already working as data scientists at companies of all sizes. Dubbed “the sexiest job of the 21st century” by Harvard Business Review and the “best job in America” by Glassdoor, the role of the data scientist is in high demand as organizations desperately need professionals who can organize the astonishing amount of data that is being generated as well as prepare data for analysis.
Data science is now appealing to more and more professionals already in a management or analytics role, particularly those interested in pivoting their careers for the new digital age. According to Forbes, for most of 2016, there was an average of 2,900 unique job postings for data scientists listed each month. According to a McKinsey Global Institute study, it’s predicted that by 2018, there will be almost 200,000 open positions.
Despite the tempting and seemingly endless number of opportunities in data science, it can be difficult to transition to data science when you’ve already invested years of blood, sweat, and tears into another career path. Fortunately, there are ways to make the transition into a data science role much easier. For anyone thinking about transitioning to a data science position, here are a few things to keep in mind.
First, define your goals
A career transition is not always an easy process, and the most important thing to consider in any career switch are your goals. What are your reasons for considering a switch to data science? Are your reasons for changing careers deeply rooted in the short term or do you have long-term goals? These are important questions to ask before you can start making the necessary steps toward switching to any new profession, let alone to the data science field.
As for short-term goals, something to keep in mind is that you might not always have a lot of time to devote to learning new technical skills—especially if your team demands lots of focus on higher-level goals. Therefore, if one of your goals as a data scientist is to learn new skills continuously, you will need to dedicate time and commit to it. You may also need to get others involved to help mentor and motivate you in the beginning.
When it comes to long term goals, as you move up the data science ladder, being in a leadership position often means your role will be less technical. Leadership positions will require solid team management skills and project planning skills, and these will need to be developed over time if you don’t already have them. The organizations you decide to work with and connections you make along the way will be vital. Choosing the right ones will, in turn, help you achieve your goals should you aspire to reach a leadership position.
Start cultivating the right skills before you make a change
Typically, when we think of data scientists, we think of people who excel at crunching numbers and can handle large sets of data. But a data scientist is also someone that genuinely loves learning and helping organizations improve through data-driven decisions.
To get started, you’ll need to develop any missing hard skills, which may include statistics and analysis, machine learning, and understanding Hadoop. But you’ll also need to possess excellent critical thinking, persuasive communication, and problem-solving skills. There are many resources around the web to help you get started, as well as online courses and data science bootcamps that can help boost your skills in no time.
The important thing to remember is that, as a data scientist, you must continuously develop new skills and always be on the lookout for new challenges and opportunities. Proving that you are someone who can constantly teach yourself new skills will also come across when the time comes to interview for a data science position and send a positive signal to the company interested in hiring you that you have what it takes to succeed in a constantly evolving role.
Work data science into your current role
The good news for anyone with a business background considering data science is that the demand for managers with a strong data background is equal to, if not exceeding, the demand for pure data scientists. This means there are plenty of opportunities for business-minded professionals to transition into data science roles.
Over the years, most of the data-related projects that organizations now have on their plates require multidisciplinary teams to work together. Furthermore, most organizations that want to stay ahead of their competitors are driving their decision-making with data, meaning it’s almost a requirement now for managers and leaders to have data analysis skills on top of their existing skill sets.
If you’re interested in completely switching careers to a data science role, a good strategy is to start incorporating data science skills into your current role so it will be much easier when you make the transition. If you haven’t already, start by adding data-driven decision making into your current role. As mentioned above, it’s only a matter of time before every manager and leader will be required to have data and analytical skills, and you can put yourself ahead by starting now with your current position.
Finally, if you’re thinking about pivoting into the world of data science, emerging yourself in the community—whether it’s by attending data-focused meetups or receiving technical mentorship—can help you meet others whose career goals align with yours. Considering the points above first should also help you get a better idea of what to expect as a data scientist, and hopefully, provide you with the inspiration needed to take the next step.