Data Scientist can be anyone who is better at statistics than a software engineer; who is better at software engineering than any statistician.
Data scientist are the ones who wrangle with Big Data. They are the ones who use their formidable skills in math, statistics and programming and make (structured or unstructured) data and clean, massage and organize it into readable form.
They further use their analytical skills, industrial knowledge and contextual understanding to help solve business challenges by uncovering hidden solution and being sceptical of the existing assumptions.
Given these skills, Data Scientist is the hottest job role in the IT field. If you are looking for making a switch, here is what you need to know about how to become a Data Scientist.
Common Pathways to Become a Data Scientist
There are three common pathways for those who want to make a transition.
Enrol in a Master’s Program.
The university setting grounds students in the underlying theory. It’s the most expensive and most time-consuming option but also provides structure and connects students with employers that recruit on campus.
Below are the top Universities (in no particular order) that you can consider for taking an advanced degree in Data Scientist –
- Columbia University
- New York University
- Carnegie Mellon University
- Northwestern University
- Georgia Institute of Technology
The self-taught approach is always the scrappiest way. However, finding projects through which to apply learning and an eventual job rests entirely on the student.
Participate in a Bootcamp
At Bootcamps, typically, practitioners teach in an accelerated timeline. This approach strictly relies on their experiential learning. Therefore, projects are built into the program to reinforce learning. And to help students get placed at companies, the staffing managers have relationships with employers.
Data Engineers vs Data Scientist
While looking for a change, be very careful to differentiate data scientists from the related roles of data engineers and data analysts.
To make it clear, data engineers rely more on their engineering skills, while data scientists rely on their mathematics and statistics. And as far as business analysts are concerned, they rely on communication skills and domain expertise in their job role.
Some Tips While Making the Switch
- You can start your journey by whatever you are currently doing. Start injecting data from there
- Start by being scrappy. Develop your skills using any of the many free resources available – Coursera or MIT OpenCourseWare could be a good resource for you to start with
- Keep searching for projects to apply your learning
- Possibly go back to school for a degree program or join a Bootcamp after exhausting resources available online
- Most importantly, find a mentor, ideally, someone who has made a similar transition to make it easier for you to make the transition
Are you looking for a change in job? Let us know about it here
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