Meet the data scientist: Steve Einbender
By Anne-Lindsay Beall, SAS Insights Editor
Home Depot hired Steve Einbender to be a data architect, but he soon lobbied his advanced analytics skillset into a data scientist role, successfully building the company’s Advanced Analytics Center of Excellence. We interviewed Steve as part of our Data Scientist Series.
What’s your background and education?
Einbender: I have an undergraduate degree in experimental psychology and an MBA, with a concentration in statistics, from the University of Florida.
Steve Einbender, Data Scientist for Home Depot
What skills help you most as a data scientist?
In order of importance: domain knowledge, communications, data architecture, statistics, extraction and analytical programming. These skills are essential to do the job, but just as important are the "selling skills" to communicate the value proposition to your customer. What data scientists produce are highly specialized deliverables; they’re not commodities that everyone necessarily understands.
When did you figure out you wanted to be a data scientist? What motivated you to become one?
I consider what I do to be behavioral science. I study the behavior of both animate (i.e., customers) and inanimate (i.e., products, devices, structures) objects. I've been fascinated with behavior since I was a child. This work is a natural pairing of curiosity with data and analytical methods.
What department do you work in and who do you report to?
Currently, I work in IT and report to an enterprise architect, but I’ve also been on the "business side" for many years as well.
How long have you had your job and were you hired specifically to be a data scientist?
I've been with my current organization for almost 15 years. I was initially hired as a data architect but took advantage of every opportunity to sell an advanced analytics solution when appropriate. Being proactive with my advanced analytics skillset naturally evolved into my current role.
Do you work on a team? If so, what’s the makeup of your team?
All my customers are teams associated with different business units (e.g., store ops, merchandising, supply chain, customer, etc.). I consider myself an internal consultant that does project work with a variety of these business teams. I'm also the Senior Data Scientist at Home Depot’s Innovation Center, where I work with a team of undergraduate and graduate students on a variety of advanced analytics projects.
What’s your job like? Is there a typical day, or is each day different? Can you give us a basic idea of what you do and the kind of projects you work on?
As an internal consultant, my day-to-day focus can be very different. It's a fascinating scope of work that addresses many different analytical challenges. The central theme of each engagement is basically optimizing a business process and demonstrating value via the "lift" of the optimization. Every project entails requirements, design, data, methods, insights, application and measurement.
Is your job what you expected it to be?
This job continues to exceed my expectations in respect to the variety of engagements.
What’s your biggest challenge?
The two major challenges are always the same:
• Convincing the customer of the value proposition.
• Creating the analytical data set (i.e., sourcing, sufficiency, quality, formatting and persistence).
What’s your greatest accomplishment thus far?
Building a successful advanced analytics center of excellence. My "business" is better than ever. Technically, I recently completed a project that combined both time series regression analysis with a linear programming optimization.
What do you enjoy doing in your spare time?
My family is my priority, but I do manage to do a lot of cycling and play drums in two different bands.
What’s your favorite new technology or app?
Given the significant data scaling issues at my company, in respect to advanced analytics, the Spark platform is huge for us. I'm also very excited about SAS In-Database technologies.
- Whether you want to find out what data scientists do, hear from some real-life data scientists or learn how to become one, check out all the articles in our Data Scientist Series:
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