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The role of Mathematics and Statistics to become a Data Scientist

My Short Story

Rahul Agarwal
Aug 22 · 3 min read

Data Science is Hard. And, there is so much to learn.

When I first started with Data Science I was totally baffled by the Mathematics behind.

So What did I do?

This post is my story of how I started with Data Science. It is a true story.

A Brief Background

I am a Mechanical Engineer.

No CS Degree. No formal Math/Stat education.

Got a business analyst job in 2010. For the first three years did a lot of grunt reporting work including Excel/SQL, Spotfire.

The Opportunity

Then the opportunity presented itself and my manager asked me to his office. It was the year 2013:

Manager: I want you to learn some Python.

Me: But I have never done programming in my life. Why now?

Manager: Have you heard about Data Science? There is something called the Random Forest Algorithm that I heard about. Since you are the only non-developer around I thought you might be able to dig in(Business Read: Since you are the only one with no work on his hands, why don’t you do something)

The Grunt

So I went to Google.

Read what RandomForest is used for. Just understood a little about the classification problem statement.

Read a blog from someone who had implemented it in Python. Copy Pasted his code. Ran on my local machine. And Voila!!!

We used that small piece of code to run on a classification dataset for that company and included it in a product. My manager was impressed.

At that point in time, I really didn’t know any data science. I didn’t know about Entropy, decision trees, and Cross-validation. Hell, I didn’t even understand Linear Regression.

To tell you the truth the model I created might have overfitted as hell. But I just know that it was a start. And I consider that start very important.

From then on I started trying many models to do the same task.

I started up with Kaggle. And when I was not able to compete I started reading more.

I took many open MOOCs. I learned about new things.

I was open to learning new things. I was open to understanding new things.

The Realization

And then one day I realized that I was able to understand the math behind if I was willing to put effort.

I started up with the breadth and eventually got into the depth of things.

So yes, get your start. Get your hands dirty.

Run the algorithm/s. Try to improve them by playing with the parameters and reading up about them.

I am sure in the process you will learn a lot about the inner workings of the algorithms.

And maybe then someday you will be motivated enough to understand them fully.

Thanks for the read. I am going to be writing more beginner-friendly posts in the future too. Follow me up at Medium or Subscribe to my blog to be informed about them. As always, I welcome feedback and constructive criticism and can be reached on Twitter @mlwhiz.

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Rahul Agarwal

Written by

Bridging the gap between Data Science and Intuition. Data Scientist @WalmartLabs. Data science communicator at mlwhiz and TDS. Connect on Twitter @mlwhiz

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