Can Non-STEM Graduates Be Data Scientists?
Due to the overflow in generated data today, data scientist jobs are one of the most desirable jobs to aspire for. Good data scientists dig deep into data, analyse it and predict outcomes that can be crucial for business decisions. But being a data scientist is not a cakewalk. It requires a combination of a diverse skill set that gets you hired. These skills include a solid grip over mathematical and statistical concepts, a good hold on programming, a solid understanding of what businesses and clients want from the data and the ability to see through data. This may sound like one needs to be from a STEM (Science, Technology, Engineering, and Mathematics) background to even dream of being a data scientist. While a lot of data scientists do come from tech or math-oriented backgrounds, that should not discourage you from aspiring to be a data scientist. However, the journey can be more difficult and needs a lot more effort than someone who already comes with mathematical and coding knowledge. But it is not impossible and can be done with proper guidance. Here are a few suggestions that can help someone from a non-STEM background make an entry into data science: Learn the fundamentals well If you are coming from an economics, commerce, or business administration background, certain aspects of data science are already covered in the courses. One has to identify these areas and then figure out where there is a lack of knowledge. Certain courses may not focus on deep mathematical and statistical concepts, which are fundamental to data science. A non-STEM student has to identify these areas and take courses or read to develop expertise in these. This may not happen overnight and can take quite some time, but it will reap benefits in the long run. Rizul Goyal, who is an economics graduate and works as a data scientist now, says, “The will is the only must-have. It can sound like a book quote, but I was determined, and I learnt coding in 3 months. I don’t know why anyone should limit their career choice on the basis of what they studied in graduation, given the fact that most of us don’t have proper career counselling in our initial school days. I was fond of mathematics and statistics from my school time, so maybe it got a little easier for me, but it’s not a must. When you plan to get into data science and start learning, focus on your basics and focus on implementation a lot. Do a lot of experiments. Whatever you are doing, go in-depth. Try to work on some experiments by taking real-life examples.” Pick up tools/ programming skills Data scientists use a variety of tools that can help them comprehend the data better. They use packages like R and Python to derive interpretations from the massive data sets they handle. For someone from a non-tech background, it may seem intimidating to pick up these tools first. But one has to move ahead from this fear and take the initiative as this is a crucial step. Taking a few online courses or offline classes can easily help you get introduced to these tools. After that, one has to constantly work with these tools and use them in projects and real-world applications to get a true feeling of handling an analytics job. Find a mentor Finding a great mentor can help to make this uphill journey quite smooth. A mentor can be someone who has already shown this path to others and can lead you to a similar destination. In today’s world of social media, one can easily find people who can give them the right guidance to enter the data science field. But one has to find mentors as per their needs and not just popularity. Once you find the mentor, do not be hesitant to ask them all your questions, however small or big. Accompanying them to networking events, seminars, and boot camps can only add to your knowledge and help you get started in this domain. Venkat Raman, the co-founder of Aryma Labs, says, “A good mentor is one who is able to judge the students’ aptitude and skill level. Based on this assessment, the mentor then has to devise an optimal learning path. Initially, non-STEM students might feel overwhelmed while learning all the mathematics and statistics concepts. It is the role of a mentor to motivate the students and dissuade them from giving up. Start with Data Analyst and Business Analyst roles As being a data scientist requires a mix of different skills that may take years to master, a good way to start would be to take up data analyst and business analyst roles. While working in these roles, one needs to put in a lot of work to pick up the essential skills and move into a data scientist role after a certain amount of time. Raman adds, “Many private courses and data science gurus may narrate stories of people transitioning directly from non-STEM to data science roles. I am highly sceptical of these stories. From my experience, the transition is rather very tough. However, the strategy of starting as a data analyst and then growing into a data scientist role is ideal. In fact, I have seen some people start as data analysts, and after 4-5 yrs they transition into a data scientist role. It is possible; however, it requires a lot of dedication and effort.” Try to get a Master’s/ certification in a related field So, you do not have a Bachelor’s degree whose knowledge can help you in data science. Why not get a Master’s degree directly aligned to cater to your data science dreams? There are so many universities, both in India and abroad, that offer you full-time masters in data science, AI and analytics. If you have the time to pursue these full-time courses for mostly two years, it can help you build a strong foundation in the data science domain. If you do not have the time and opportunity to let go of your job, you can always go for a certification course available online or offline, but one has to be very careful while choosing these courses. Enquire properly about faculty, mentors, institute, and content structure before taking admission in such courses. Take part in competitions and hackathons; build your profile Put yourself to the real test once you get a decent amount of exposure to statistical concepts and a good hold on a particular programming language. Take part in different competitions and hackathons and put your knowledge to the test. This will be a great confidence booster and will add value to your resume. Mindset is everything If you have a burning desire to become a data scientist and come with good critical thinking and analytical skills, no one can stop you from achieving your dream career. Yes, it may take longer, but you can surely reach there as many have. The key here is to keep the mindset strong and focused and work on analysing yourself. The areas in which you lack would require focused and dedicated attention. Keeping these steps in mind and actively trying to improve yourself will surely help you bag a data scientist role.
Getting into data science with a non-tech background
Getting into data science with a non-tech background
["competitions", "Hackathons", "mathematics", "mathematics and statistics", "Python", "STEM"]
["mathematics", "data science", "Go", "competitions", "programming_languages:R", "STEM", "AI", "R", "Hackathons", "programming_languages:Go", "RAG", "Python", "analytics", "programming_languages:Python", "mathematics and statistics"]
["AI", "data science", "analytics", "RAG", "Python", "R", "Go", "programming_languages:Python", "programming_languages:R", "programming_languages:Go"]
I am a technology journalist at AIM. What gets me excited is deep-diving into new-age technologies and analysing how they impact us for the greater good.

Reach me at sreejani.bhattacharyya@analyticsindiamag.com