Transitioning to a data science career

KDNuggets ought to be a regular stop. Here is an article about transitioning to a data science career, or at least part 1.

How I started

I started as an engineer at a high security facility. I had already demonstrated that I was very effective with PCs – while onsite waiting for my interviewer to free up I noticed someone struggling and fixed his problem on the spot. It turned out that although it was an engineering job, the boss’s biggest pain point was PCs. Yes, the interview went well…

It was a very expensive getting people screened through security, so I wound up getting a mainframe assignment. On a short deadline, from a boss who didn’t like contractors like I was, with no access to or even knowledge of what to ask for, having no knowledge of CLIST, SAS, TSO, ISPF or other mainframe staples, and only a phone number for another guy at another facility to help me out. And he was hard to catch (no email then, no web unless you count Compuserve et al on dialup, no Amazon – yes, I’m that old).

Fine, I learned enough mainframe and SAS skills in time to survive that, and now other assignments requiring those new skills came in. Before long I was no longer doing engineering work and I continued to add to my skill set. Next thing you know I’m doing more mainframe SAS, but for another domain.

Next steps

By now I had experience in a couple of domains and I had taken a COBOL class. For the next gig they were desperate for help and I had domain knowledge. The interview was something like this: “Do you know AS/400s?” “No”. “Do you know COBOL?” “I just finished a class at a community college”. “You’re hired!”. If I had read the req I wouldn’t have bothered applying, but the recruiter knew what he was doing.

It worked out well for all concerned. AS/400s weren’t in the plan, but later they became useful – SAS wouldn’t run on them so I was likely the only SAS person around who knew anything about them.

Variations of this happened over and over – there was a req that wanted certain skills, I had most of them, I got the job and learned the rest the skills, repeat. And I kept looking ahead for strategic skills to develop to steer my career – that’s what got me started with R, Python and many others.

Soft skills

I had become very strong and broad technically, so my soft skills were the weakest part of my game. I had been hearing about Toastmasters for years, but it never was convenient enough to suit me. When a club started at my workplace I joined. I wish I had done so years before.

Shortly I realized how much more I could learn about soft skills like mentoring, networking and leadership, how all of these depend on good speaking and presentation skills, and how Toastmasters could help. It’s self paced so you can progress as your life permits. Check them out – it’s the best deal you’ll ever find for personal and professional development and there’s probably a club near you.


Whether Toastmasters is your thing or not, you want to find and maintain mentors. They’re out there for every aspect of your life for every period in your life.

If you’re not humble enough to admit you need mentors, or at least can use them, that’s a problem. The humbling is coming – best to do it sooner rather than later, and in private rather than in public.

Go your own way if you insist, and by all means don’t pester mentors – make an effort to solve your own problems, so the mentors don’t feel like babysitters. But get help before you need it, and start building those relationships now.

And know that a few critical bits of advice at the right time can greatly change your life and career. It definitely would have for me.

Enough sermonizing for now. At least until they publish Part 2…

UPDATE: Part 2

Author: dsnovice

Engineer, Toastmaster, healthcare analyst, data science novice, web development novice

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