What are some of the most important attributes of a good data scientist? If you do some research, you will often find that beyond the technical prowess in math, statistics, and computer science, you also need to have good communication and storytelling skills. A good data scientist must be able to explain the complex math and statistics to non-technical decision makers without compromising the rigor and accuracy.
Today I’d like to tell you another story that happened about 7 years ago, in the early days of my data science adventure. This is, however, related to the last post, because quite a few people have asked me how all the research works in computational neuroscience relate to what I am doing now at Lithium.
I’ve been pretty much off-the-grid for the past couple of months, and there are good reasons for this. I’d like to tell you why, but I’d also like to continue the next episode of my data science adventure. So I am going to attempt to do both.
Remember when I said that I have only 2 missions in life as a scientist?
knowledge creation—doing good research to advance the field and industry
knowledge dissemination—communicating the result and educating the industry about the research, so they can use it to actually move ahead
Much of my time is spent between these 2 different modes of work. This is an old habit that has been with me for a long time, ever since I was in college.
Before I continue to the next stage of my data science journey, I thought it would be nice to discuss “what is a data scientist?” This is very timely, because “Data Scientist” is a fairly new role, and it’s somewhat confusing in the industry. In fact, I’ve just participated in Experian Lab’s #DataTalk last week to discuss this very topic.
Previously, I shared with you the story of my circuitous adventure from academia to industry. I followed where the data led me and went from analyzing particle physics data, to brain response data, and then to consumer behaviors data. Yet, that was just the beginning of my journey to becoming a data scientist; it only got me in the door. While it’s how I joined Lithium, it’s not how I became a data scientist.
I thought I’d ease into this more technical subject by answering a question that I get asked many times: “how did you end up as a social media data scientist from your biophysics PhD background?”
Retrospectively, I have literally answered this question (in one form or another) over 100 times, with journalist/blogger interviews, in keynotes Q&As, or just casual conversations with colleagues or acquaintances.
I normally don’t do any conference recaps, because I speak at so many of them throughout the year. However, this year’s GSummit was quite unique, and I took away something big. It’s not what most people would have expected from a conference—it isn’t new knowledge, new opportunities, connections with new people, or reconnection with old friends, but something more inspiring to me personally. If you are interested in what is it that I took away, then read along as I tell you more about this conference through the narrow spectacles of a scientist.
Welcome back. This is the 3rd (and final) installment on my reactions to the Klout acquisition. Last time, I described possible ways we could leverage the combined expertise of Lithium + Klout. These are exciting possibilities that are highly disruptive and transformative, but how did we get here? I’m certainly excited by all the new possibilities ahead, but there is a more personal reason for my enthusiasm. Today, I’d like to share the human side of the story. It’s a story of how we got to where we are. That way you can truly understand how I feel and appreciate what this acquisition means to me.