From Mechanical Engineer to Data Analyst: A Successful Career Launch

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

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 years 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, which was way faster and more efficient. At the same time, he also learned 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 course for 6 months that also makes one industry-ready. Moreover, he always wanted to learn new technical skills 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 anytime 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 a fair knowledge of math and statistics, but one need not be a pro!

2. Data Science is not a very tough subject but, indeed, a very vast subject that needs a lot of focus, patience and practice. One has to take time to practise every skill like programming, problem-solving, presenting graphs etc.

3. Advice for all non-tech aspirants is to practice one's subject rigorously. Concentrate more on Python and SQL. Try to solve as many questions as possible.

4. Focus on your projects, as most of the questions in the interview will revolve around the project.

Mayur's Inspiring Interview