Last week, Tricia Rhodes kicked off a new Q & A series that shares how SingleStone is redefining the consulting industry. Through a human-first approach and a team of experts, we’re convinced that we can debunk some of the common stereotypes and help you think differently. This week, Vida Williams, TedTalker, professor, and community leader extraordinaire, shares why she chose to join SingleStone, the necessary data science skills, and what excites her about leading the Data Solution at SingleStone.
Get to know Vida Williams, Advanced Analytics Solutions Lead
Q: From Ted Talks, to non-profits and teaching university courses, on top of leading our Data Solution, you do a lot. You must get a lot of people asking for advice…what are some necessary data science skills?
A: Absolutely. I get a lot of young people with a similar statement: “I’m taking math and statistics and coding because I want to be a data scientist.” My reaction is always the same – “that’s great because you’ll learn the disciplines and the mechanics of what we do as data scientists. But the most important data science skills? The ability to understand people.”
I often recommend that anyone interested in becoming a data scientist take a social sciences course. Why? Because the key to understanding data is understanding that every data element that we look at is emitted from some human interaction and you can’t contextualize the data unless you understand what spawned that element.
Ok let’s get futuristic, what’s next for data science?
I think we’re just starting to hit our stride with data. We’re approaching new frontiers that make it super critical that the people who work in data, do so from a humane perspective.
I believe it’s incumbent upon us as data scientists and data practitioners to keep top of mind that we are emulating ourselves and our decision making so that we don’t misguide ourselves later. These conversations are happening in the broader marketplace and with our own clients. It’s an exciting time.
You make complex ideas like “data wrangling” seem almost exciting, how do you do that?
A: Data wrangling is the foundation of what we do, and while it’s not the sexiest, I find it the most exhilarating because it’s there that you start figuring out whether you can answer big business questions. It’s like solving a problem, but many, many times over. As a technologist, I love it.
And yes, it’s difficult to work with the large volume of data that we support as consultants, but really, the most difficult part from an industry perspective is that we don’t know where we need to be in terms of accountability.
So, accountability is tougher than data wrangling?
In some cases, yes. Let’s say I put a team of machine learning engineers together and they’re writing an algorithm for a payer or financial institution, and for arguments sake, it led to an insidious outcome, a bias of some sort…who’s actually to blame for that? Is it the business owner or is it the practitioner or is it the enforcer of the outcome? Because we don’t know where that responsibility lies just yet, it makes it very difficult and sometimes a little scary to write things that you’re not entirely sure where the outcome is going to be.
So, I try to make sure the practitioners that work on my teams balance those two things together, doing the work, but then also being accountable for the work.
Speaking of teams, what motivates you to lead SingleStone’s Data Solution?
I’ve never worked in a place where people actually work with the best of intention. In a similar way to how I approach data, with a social science, human-based methodology. At SingleStone, people mean what they say and they’re well-intentioned. That doesn’t mean we get along 24/7 and everything runs perfectly…it means that you really can, even in disagreement, find solutions and a common understanding because, at our root, we’re each coming from a positive place.
In the same vein, I love the level of intellect and talent. This group is really unique in their sheer volume of brains and an equal volume of creativity. I feel like when you get that combination, you can really give birth to groundbreaking innovations on behalf of our clients.
How does your organization manage its massive amounts of data? Are you using it to generate real insights and better your future? We want to hear your approach. Comment below and don’t forget to sign up for our newsletter!
The series continues next week. Until then, be well.
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