by Mark Sellors, Mango Solutions @sellorm 

Mark Sellors from Mango took the Data Science Radar Challenge and his dominant skill was a Technologist, so we asked him a few questions.

1.  Tell us a bit about your background in Data Science.

I guess I got my start writing bespoke reporting tools for a previous employer. This work was on the job ticketing system used by my department, and enabled a much richer understanding of the amount of work being undertaken by the team. I then moved on putting together report packs for use by management. Officially, I was a working as a Unix systems administrator, so I was also looking after very large scale compute clusters and ensuring that massively parallel workloads such as ETL and huge reporting jobs could run unhindered.

2.   How would you describe what a Technologist is in your own words? 

I think that a technologist is someone with wide ranging technical experience and knowledge, and who is able to apply that knowledge appropriately as the opportunity arises. Being the first to know about a new, up-and-coming technology is part of it, but the implementation side can’t be overlooked. Technologists need to be flexible and able to learn on the job, there are no one-size-fits-all solutions in Data Science.

3.  Were you surprised at your Data Science Radar profile result?   Please explain.

Not at all surprised! I see my self as a technologist and I think my colleagues view me the same way. Of course, it probably helps that I had a hand in the design of the very early internal versions of the radar that have been expanded upon into what you see today! I was surprised that ‘Communicator’ came out so low, I’d have thought that would have been stronger than ‘visualiser’.

4.  Is knowing this information beneficial to shaping your career development plan?  If so, how? 

Even though I had a good idea of what was coming, I think it’s still helpful. Of course you could argue that pigeon-holing people like this is counter productive, but the radar was never intended to be definitive, or to limit people. For my part, being able to see my strengths in that radar chart has really helped cement something about myself that I always knew, but was never necessarily that good at articulating. It also highlights areas where I’m perhaps weaker. Some aren’t hugely important to me at the moment, such as ‘Visualiser’ and ‘Modeller’, but I’m always keen to improve my communication skills, so I’ll be working on those over the coming months.

5.  How do you apply your skills as a Technologist at Mango Solutions? 

As Mango’s Technical Architect on Data Science projects, I work primarily in the Data Engineering space. Need an environment to do analyses with Spark and R? Or a system to perform massively parallel mortgage analyses? Perhaps you’re looking to design and deploy a Data Science Lab ? Maybe you need a Hadoop environment to store and analyse huge amounts of data? I’ve been involved in all of these and many more over the past few years, from simple installs of RStudio Server, to designing and building large scale data processing platforms.

6.  If someone wanted to develop their Technologist skills further, what would you recommend?

For me, one of the main personality traits all good technologists have is a willingness to roll up their sleeves and get on with things. There was a time, when I knew nothing about Hadoop, or about R or whatever it is, but I never let that hold me back. Want to learn about Drill? Download it, read the docs, and just get on with it! It’s rare in this world that we’re afforded the chance of learning something which we can then spend the rest of our careers carefully applying over and over again, so mucking in, asking ‘stupid’ questions and working with people smarter than you are essential to getting out ahead of the curve and staying there.

7.  Which of your other highest scoring skills on the Radar compliments a Technologist skillset and why? 

It’s no surprise that ‘Programmer’ and ‘Data Wrangler’ are my next highest scoring categories. I spent 7 years working on databases and ETL systems. On the programming side, as a systems administrator and someone who loves ‘tinkering’ with this kind of stuff, having a grounding in programming concepts is invaluable. I’d be the first to admit that I’m not the worlds best programmer, far from it, there’s so much to learn, but I’m more than capable of getting the job done when the need arises, and plenty good enough to make spending my life working with these technologies much easier!

Want to find out what you are? Do your own Data Science Radar here  and share your results on Twitter.