Challenges Faced in Data Science Careers

By POOJA BISHT |Email | Mar 13, 2019 | 7440 Views

It is true that there are a number of opportunities for people involved in Data science, with jobs increasing into the field every day. According to a report published. in India, there were around 50000 jobs that were vacant for Data scientists and Data analytics. This makes Data science an exciting and growing career to choose indeed.

While there are always benefits of knowing the importance and usage of Data science in numerous sectors today and in increasing online businesses, its also noteworthy to know the major challenges that a Data scientist face so that if you are into the job of Data science already or moving your career ahead in the field it would be a plus point to you to already know the major challenges and ways to deal with them.

  • Developing Motivation

Nobody ever talks about motivation in learning. Data science is a broad and fuzzy field, which makes it hard to learn. Really hard. Without motivation, you will end up stopping halfway through and believing you can not do it when the fault is not with you its with the teaching. Take control of your learning by tailoring it to what you want to do, not the other way around." Vik Paruchuri, Founder, Dataquest. It is indeed the truth. Getting into the field of Data science which will actually take a lot of your time in working on the data, sitting for the long hours to generate information motivation is the only thing that will take control of your tiredness and will make you work in a hard time of quitting.

Develop your passion for the Data and see your work as an opportunity to generate high revenues for the company and developing personally at the same time.

  • Lacking Skills
From the many challenges in a data scientist job, lacking skills in candidates is one of the prominent faced by the companies. There are many seats which are vacant for the required post of Data science but with the dearth of talent the vacancies are not getting filled. If you are into developing your career into the field its a time you develop the right set of skills and start to learn the basics and in depth of your role to prosper your career into the field. 

  • Finding Objectives  

Scott Hoover, director of data and analytics at Snowflake, says, Having a mental model for ones objective before touching any data is incredibly valuable. Instead of aimlessly fishing for signals in the data, thinking like a scientist by formulating hypotheses that are founded on some formal model of human behavior, economics, systems, etc. and then testing those hypotheses make for more successful data-science applications.
People who get involved in the role of Data scientists and start working with the Data without being actually known of the objectives of their company make the situation troublesome and waste. Avoid it! Know about your stakeholder's and the company's objectives and try to explore the data then.

  • Communication

Data scientists into the role or aspiring for often ignores the importance of communication in their field which they have to show in dealing up with stakeholders, departments, non-technical audiences. There is a brief article I have also shared of communication problems in Data science job, I advise you to please have a look on it to see how communication could make you more eligible for a Data Scientist role.

I hope you got to understand some of these challenges that I laid in from of you in Data Science. These were some of the top challenges I came across. I hope it will give you an edge over your career.

Source: HOB