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Data science has been one of the most attractive fields to work for the past decade and change. The area is evolving at a rapid pace. What a data scientist was doing a couple of years ago has already been automated or is on the verge of automation — the goal post is moved at every turn.
“Automation is no longer just a problem for those working in manufacturing. Physical labor was replaced by robots; mental labor is going to be replaced by AI and software.”Andrew Yang
Data science job market is highly competitive. The survival of a data scientist rests on the Toffler mantra: Learn, unlearn and relearn.
Here, we look at what it takes to stand out as a data scientist in 2021.
Jack of all trades doesn’t cut it anymore. While data science has many applications, people will pay more bucks if you are an expert at one thing. For instance, your value as a data scientist will be worth its weight in gold if you are exceptional at data visualisations in a particular language rather than a bits and pieces player. The top technical skills in demand in 2021 are data wrangling, machine learning, data visualisation, analytics tools, etc.
“‘Jack of all trades, master of none’ is an idiom that’s becoming pervasive in development. The idea goes that a developer who dabbles in everything cannot be amazing at anything.”Parker Software blog
As a data scientist, it’s imperative to know your fundamentals down cold. It would help if you spent enough time with your data to extract actionable insights. A data scientist should sharpen her skills by exploring, plotting and visualising data as much as possible.
Most data scientists or aspiring data scientists doing statistics learn to code or take up a few machine learning or statistics classes. However, it is one thing to code little models on practice platforms and another thing to build a robust machine learning project deployable in the real world. As a rule, data scientists need to learn the fundamentals of software engineering and real-world machine learning tools.
“No machine learning model is valuable, unless it’s deployed to production.”Luigi Patruno
Know Your Math
One of the most important things for a data scientist in 2021 is to keep updated with the latest development in mathematics. This is crucial if you want to build state-of-the-art machine learning systems. Most frameworks will let you easily build models or networks without having in-depth knowledge of mathematics. But, if you want to stand out as a data scientist, a strong foundation in calculus, linear algebra, and statistics is critical.
“I have always been a strong advocate of self-learning, and I believe that is where you get maximum value”Dipanjan Sarkar
Build A Portfolio
If you are looking for a job, getting to an interview might prove very difficult. There is so much competition, and the options for a recruiter for data science roles are endless. What can help you stand out is a robust portfolio with various data science projects. A good Github portfolio on your resume can help you get noticed. Target at least one open-source hands-on project every month to keep your portfolio updated.
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“Sometimes, even getting to the interview can be difficult. This ties in well with the example given in the last tip. There’s nothing more powerful on your application than evidence that you have done this kind of work already”Dr Adam Sroka
A data scientist should keep abreast of the latest research in the field. That said, original research is always a huge plus. The best way to do this is to publish research papers in well-known journals. The proof is in the pudding. Ideally, you should aim to publish at least one research paper in six months.
Join A Community
There are various Slack channels or Meetups to stay up-to-date with the latest happenings in the field. Joining a community will help you remain connected and give you visibility.