Insecurity is good

Let's start with a series of questions

• Are you the smartest person in the rooms (virtual or real) that you were in this year?
• Do you need to consciously think what you needed to learn (as opposed to what you wanted to learn) this year to do your job?
• Are you comfortable and secure in your knowledge of how you do your job?

If you answered no to any of those, welcome to the club. Insecurity has earned a bad name, but a healthy dose of it is better than its complete absence. I have been insecure most of my professional life - treating career as a lab with experiments (often controlled) and learning for the sake of learning.

The early career insecurity - tools and processes

I started working in 2007 in thermal system design, a key and in-trend component of which was computational fluid dynamics (CFD). My experiences with the field

• I was exposed to CFD back in 2004 by the means of a college project,
• followed by further coursework along with conferences,
• as well as elective and audit courses and a well appreciated final year project

This meant a total of 3 years of academic background and interest. I was comfortable enough with the mathematics to hold a presumably :-) intelligent conversation. Still didn't feel secure walking into that first job after the first week.

My 6 month long Bachelor's work could be reproduced in a week with the tools available in my first team.. by me.. as a side project!

This insecurity stayed with me, ebbing high or low depending on the role at the time, but it was always there even as I grew in technical depth and roles. Often the roles were consciously chosen to increase the insecurity. At a point though, the answers to the questions at top started to move on the spectrum, and in came the data domain!

The ever increasing mid career insecurity

In data domain as well, lack of familiarity with best practices and an ever changing tech stack led to insecurity though with open source adoption, it seemed to play a lesser role. In my current role since last four years, the insecurity has continued and of late started to increase.

Data science, from my perspective, in its current state is relatively new.

In 2008,

• Dr DJ Patil and Jeff Hammer-bacher, heads of analytics and data at LinkedIn and Facebook respectively, coined the term 'data science' to describe the emerging field of study that focused on teasing out the hidden value in the data that was being collected from touch-points all over the retail and business (note the specific domains!)
• I was already working for around a year, coincidentally going through a six sigma certification and a learning by numbers course on probabilistic design in General Electric - this was fundamental statistics).

And in 2011-12,

• the landmark NIPS deep learning paper was published by Geoffrey Hinton and co.
• when I had just started with test design, sampling a design space and design of experiment (coincidentally using R - which I continued to use for years).

Then, happened transformers, GPT-n and language models, starting 2017-2018 and it still continues to explode, as I struggle to bumble my way through it.

The field is fast changing and continuously evolving. That's probably another reason for continuing insecurity.

..embracing insecurity and working through it, is what makes a career lab interesting.

What do you think?