You are not too old to become a Data Scientist.

Original article was published by Moeedlodhi on Artificial Intelligence on Medium


You are not too old to become a Data Scientist.

Why making a career transition is not the end of the world.

Photo by NASA on Unsplash

Graduated in 2017, Worked multiple jobs, visited a foreign country, started my freelancing business, learned a new language, and most recently, dove deep into the world of Data Science.

6 months ago made the transition towards Data Science at the age of 26, Got a lot of criticism for lacking “stability” in my career, and was told numerous times that is was a bad decision because:

  1. Companies need “fresh” graduates for junior-level roles.
  2. Companies need experienced individuals for senior-level roles.
  3. You don’t have the right degree
  4. You have 3 years of experience on your resume which has NOTHING to do with Data Science.
  5. Your lack of stability shows your lack of commitment to one field.

I didn’t take this criticism the wrong way. All of the above is after all true and does describe my reality.

But I still wanted to become a successful Data Scientist

I can’t make myself younger, I can’t go back in time and alter my career path, I cannot change what has already happened.

What I can do is move forward, take steps towards my goal, and hope for the best. And that’s what I am doing.

May 2020

Started a course by Andrew-ng “Introduction to machine learning”.
Completed half of it and then shifted to a Python course for Data Science and Machine Learning.

Learned about the basics of Python, Pandas, Numpy, Seaborn, Matplotlib, and more.

June 2020

Completed the course in mid-June 2020 and then moved towards learning important statistics.

Started a book by the name of “Introduction to Statistical Learning”.

Learned about different Machine Learning algorithms such as Linear Regression and Decision Trees. Got to know extremely important concepts pertaining to Statistics such as Inter Quartile Range, Z-score, and more

July 2020

Started applying for internship roles like crazy. Messaged any and every person I could find on Linkedin who was involved in Data Science and requested them to give me an opportunity.

Finally got my breakthrough when one company offered me an intern role which was unpaid but I could care less. I just wanted to move into the field and gain experience as soon as I possibly could.

August 2020

Gained my first hands-on experience on a Real-Life Data Science project. Actually learned how to extract data from databases using SQL and how to actually implement machine learning algorithms to provide value.

Learned how to build interactive dashboards that communicate findings accurately and swiftly.

September 2020 — Present

Worked and still working with people who are younger than me but that
doesn’t matter.

The only thing that matters is PRODUCTIVITY and by that I mean:

.How punctual are you?

.Are you a team player?

.Do you have the ability to admit your mistakes?

.Are you a good communicator?

.Do you have the ability to lead?

These things matter and only these differentiate a “great Data Scientist” from an average one regardless of age, size, color, or gender.

Conclusion:

This was a rather short article but that’s because I wanted to share my experience on How I made progress in this field of Data Science. At the end of the day, what matters is your ability to make decisions and then stick by them. That’s what truly matters.