Successful Career Transition Of A Mechanical Engineer to Data Analysis!

Successful Career Transition Of A Mechanical Engineer to Data Analysis!

Mayur is a successful Data Analyst at Gallagher (a global insurance brokerage, risk management, and consulting firm).

mayur pol

Mayur Pol graduated as a mechanical engineer in 2019. He started his career as an apprentice and soon became a supply chain engineer. Mayur worked for 2 yrs for a meagre salary of 2.5 LPA, where making ends meet was getting difficult for him.

As a supply chain engineer he dealt with many data sets like supply master, price master, item master etc. To analyze these data sets, Mayur used MS Excel, which was tedious. One day he saw that his colleague used PowerBI to analyze the data sets, that was way faster and efficient. At the same time, he also learnt that some of his friends were pursuing data analytics. He got curious and explored more about data analytics. 

Mayur's Data Science Journey at OdinSchool

Now that he has decided on his career path, he started exploring courses that could teach him data science. Mayur came to know that OdinSchool offers a very comprehensive data science bootcamp for 6 months that also makes one industry-ready. Moreover, he always wanted to learn a new technical skill with respect to data science and artificial intelligence. 

When he got himself enrolled in the bootcamp, Mayur felt very insecure. He was apprehensive about programming due to his non-IT education. However, the trainers at OdinSchool, who could be reached at any time for a 1-on-1 engagement, immediately set his worries to ease. They gave him thorough explanations and several tools for understanding. He continued turning in tasks and, with the mentors' advice, improved on his weaknesses. Mayur soon attained a Professional status. 

You might also want to read, From 12 Interview Rejections and a 4 yr Career Gap to a Successful Data Scientist!

Mayur's Insights

  1. It is a myth that one has to be a pro at math/statistics to learn data science. One needs to have fair knowledge of math and statistics but one need not be a pro!
  2. Data Science is not very tough subject but indeed a very vast subject that needs lot of focus, patience and practice. One has to take out time to practise every skill like programming, problem solving, presenting graphs etc.
  3. Advice for all the non-tech aspirants is to practice one's subject rigorously. Concentrate more on Python and SQL. Try to solve as many as questions as possible.

    Don't play it until you get it right, play it until you can't play it wrong.
  4. Focus on your projects as most of the questions in interview will revolve around the project.

Found this story inspiring? Want to build your own version of this career success story? Join OdinSchool's Data Science Bootcamp today!  

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