Data Science Radar – Visualiser Profile

December 8, 2015
By

(This article was first published on Mango Solutions, and kindly contributed to R-bloggers)

by Kate Ross-Smith, Mango Solutions @LaSystemistaria

Kate Ross-Smith

Kate-ross-smith-data science-radar-mango-solutions

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

I’m not sure I have one. I trained as a Design Engineer and then a Systems Engineer, and up until now I’ve worked as an engineer and a project manager. In both of these roles, most of the time you’re analysing existing operations or processes, and presenting that back to someone who makes some kind of design or support decision. That’s kind of what data science is, I suppose.

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

Someone who thinks in stories and images; who sees the interconnections between things, rather than just in isolation. Someone who communicates most instinctively through diagrams and pictures.

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

Yes. I would have expected to be a stronger programmer, as I have a wide range of experience of different languages (but I’m not deep in one area), and I pay close attention to detail and rules; I love writing good, clean, elegant code.

I also scored high on the modeller axis… and I’m definitely the least experienced and least educated on this within the whole of the consultancy team. I would definitely expect to be a higher technologist and programmer than modeller.

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

Not really. I already know what I want to improve, and where I want my career to go. I have also spent a lot of time with more tried at tested methods, and understand my strengths quite well. I also prefer to think in terms of high-level skills rather than specific application, and this is just testing to one application.

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

I really don’t know. I’m not sure I do. It depends what you mean by Visualiser (I’m not sure it’s the same as what I mean). Making simple powerpoint presentations, I suppose. Creating diagrams (for presales and projects like ValidR) to communicate complex processes to the project team.

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

In a project setting, make sure you always know why you’re doing any piece of work – what problem are you trying to solve, and how does what you’re doing feed in to that; find out what’s been done before, and what’s going to happen afterwards so you have a good understanding of how your work fits in to the story.

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

I only had one other high-scoring skill, and that was modeller. And I really don’t think I’m a great modeller, so I don’t really know what to say. I think if you’re a good communicator and a good visualiser, then you can question people about their models and present the information in an easy-to-digest kind of way. I think that’s something I’m quite good at. I would have thought if you’re a good modeller, you spend a lot of time in the details of the model, so it would be difficult to visualse that well (because you have to let go of certain details in order to visually-communicate things well). So maybe if we pretended my communicator was higher, then that might be a good answer?

Do your own Data Science Radar here 

datascienceradar

 

 

 

 

 

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