The Journey of a Data Scientist

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Expanded post by demand – https://lnkd.in/f7Ckk56

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I began my data science career 15 years ago in 2004. First I learnt SAS. It was tough to learn coding as I had not done coding before in my MBA or my Mechanical Engineering. I remember coding from 830 am to Midnight one day. Most days I coded in SAS for twelve hours and ate lunch on desk. I used to remote submit code to Oracle datawarehouses and analyzed the then huge number of 150 gb. I did this both as an analyst in GE Consumer Finance Bangalore, and then as a manager in WNS Global Services. We were the first analytics team in WNS Knowledge Services and I transitioned projects for GMAC Insurance (arm of GM). I continued the journey with consumer finance data for Citi. The data pulled by SQL and analyzed with SAS.

That lasted me till 2008. I then learnt R. That got me to 2015. R was totally different than SAS due to object orientation. I shared my learnings in two books on R for Springer.

Then I started using Python. I didnot want my career to be dependent on one language only. Once again I wrote a book and did consulting assignments in both R and Python.

In 2017 I started with PySpark. It was fun but slightly different from Python. MLlib in PySpark was different from Sci-kit learn in Python for Machine Learning

I really really love how data science means continuous learning , as learning is fun. Yes I still enjoy coding.

We data scientists are also lucky to be in a high demand career. We get paid to have fun, to play Sherlock Holmes with data and get higher than average salaries.

Someone said Julia was promising. I checked it out a bit too. What is amazing is how SQL is still the most useful data science language. In 15 years SQL has endured.

2004- Present – SAS

2004-Present -SQL

2008-Present-R

2015-Present-PyData (Python Data Science)

2017-Present -PySpark (Python with Spark Big Data)

What will happen next 🙂