Berkeley Data Science Group / Self-Employed
Tell us a bit about yourself.
I am coming at data science from a slightly roundabout way, having produced a lot of data from academic randomized controlled trials, product development, and remote sensing gigs in my previous career as a water and sanitation engineer based mostly in India and East Africa. Over the past decade, while still important, data creation has started taking a back seat to the necessity to process and learn from the troves of data being created with greater frequency from developing countries, and I feel that — given my learned experience — I would add more value and maximize my impact by harnessing the tools of data science in this arena.
At what school and in what concentration did you receive your undergraduate degree?
I have degrees in Chemistry and African Studies from Amherst College, and a master’s in Environmental Engineering from MIT.
Why did you choose the I School?
Going into the MOOCs world of data science, I quickly realized that I needed guidance, team collaboration, and — most importantly — deadlines to really accomplish the task of becoming a competent data scientist in a few short years. At the same time, we had just had our first kid and were moving to India for a full year, so the online flexibility was necessary. It doesn’t get much better than an early morning class section followed by a long day of looking after an adorable toddler. I highly recommend that schedule if you can swing it!
What is the I School's advantage?
The I School is what you make of it, so go get it! There is a great group of faculty and students here, many of which are eminently available to talk and give feedback, and they routinely go over and above to make sure that you understand the material.
What has been your favorite class at the I School and why?
Experiments and Causality really firmed up a lot of in-depth concepts that I have been working with for a while now. It was great to get the full picture from study design through to the intricacies of dealing with loss to follow up, etc., with a focus on developing country economics built-in to match my interests.
What are your future plans?
I am passionate about evangelizing renewable energy, averting climate change, and improving global health. While the options for a junior level DS are not as wide as I would hope in those arenas at the moment, in Seattle they are growing — and so am I to meet them head-on when the time is right.
Do you have any advice for aspiring information professionals/data scientists?
Get as much exposure to the various facets of data science as you can early on as you investigate the machine learning/data science universe, as this will help you broaden the breadth of your horizons while enabling you to pick a path to dig into and develop some depth in, which is important when you go out for jobs. At MIDS, make sure to make use of your local MIDS cohort in person, and the Slack community virtually. It’s a great network.