How to get a job in data science / analytics for people coming from Commerce/Arts/Sales background

Author : Analytics Educator

I am around 30 years old and belong to a non-technical background (sales, operations, presently not working, coming from Arts or Commerce background etc.) How can I get a job in the field of Data Science?

I keep hearing these type of questions from many people. The answer is simple: you should learn these subjects well, to get a job. One should learn 3 things to start with:

  1. Statistics – Learn how statistics helps a business to make more money. In other words, the candidate should be understanding what exactly you get to know from a particular statistics (e.g. How will you be benefitted by knowing an average or standard deviation). One should be aware about the concept of statistics, rather than remembering the formulas.
  2. Machine Learning and Deep Learning algorithms – These are the actual algorithms which would help us to predict the future business scenario. There are several different algorithms (also referred as models), but there are some basic models with which one should start with (5 to 6 of them). These basic models are more in use than the other models which are sometimes used in combination with the basic ones.
  3. Software – Presently there are 3 primary software/language which are being heavily used in the data science industry; SAS, R and Python. You should learn at least one or two software well. These software will enable you to deploy machine learning and deep learning algorithms. You can start with any one of them, but with the present trend, it’s advisable to start with R or/and Python.

Seems pretty simple, huh!! What’s the catch?

One should learn these subjects well and should be knowledgeable enough like an experienced analyst. There shouldn’t be any question/topic which the candidate is not aware of. However, most of the people take this course just by believing their training institute’s false promises (unfortunately most of the training institutes make false promises like placement, and provide very superficial training), and don’t put the required amount of effort.

How should one prepare?

  • You should devote at least 1.5-2 hours a day to study and practice
  • There shouldn’t be any topic or code which you have not understood, else you will never be confident about it at the time of interview.
  • Ensure that your trainer is a Data Scientist and not some student or amateur. An actual data scientist can share their real work experience.
  • If possible, take a demo class or watch a demo video to understand the teaching style. If the pedagogy is arcane then try with other institute. (Take a demo session for R or Python or Machine Learning to judge your understanding).
  • Go through lots of mock interview with your instructor; harder the questions better would be your preparation.

End note

Start believing in yourself more, put in effort, throw away the idea that someone else will hand you job on the platter. Once you become proficient with proper skills, there’s almost a certainty that you will land up with a job as Data Scientist.