Alumni Profiles: Ben Zweig, Senior Strategy Consultant at IBM (Economics PhD, 2015) & Paul Schweigert, Analytics Consultant at IBM (History)
Ben Zweig and Paul Schweigert have each transitioned from doctoral study at the Graduate Center to successful careers at IBM. Both Zweig and Schweigert have returned to the Graduate Center multiple times to recruit for paid summer internships with IBM.
In these interviews, Schweigert and Zweig discuss their career paths and job responsibilities and offer advice to Graduate Center students considering similar careers.
Interview with Ben Zweig, Senior Strategy Consultant, Chief Analytics Office at IBM
What was your area of study at the Graduate Center, and what are your current role and responsibilities?
My area of study at the Graduate Center was Economics. My current role is a Senior Strategy Consultant in the Chief Analytics Office at IBM. The responsibilities of my team are three-fold: 1) to support units of the business in their efforts to improve performance, 2) to support IBM’s internal transformation efforts, and 3) to incubate new ideas for how IBM can become more efficient.
What is a typical day like for you?
It’s hard to say what a typical day involves. But a typical week involves: meeting with my team to discuss upcoming priorities, gathering and preparing data, brainstorming methods to empirically model certain relationships, writing programs in statistical software to examine relationships or forecast outcomes, reporting these results to management, and ultimately presenting findings and recommendations to senior stakeholders who can implement the recommended actions.
How did you navigate the transition from the Graduate Center into the career path you have taken?
Navigating the path from PhD to the private sector was challenging in two ways. Firstly, getting a foot in the door is a long haul: for positions like the one I have now, most applicants are MBA graduates; they have certain advantages over PhD students since they are more familiar with the corporate world and usually devote a lot more time into networking and staying current on business trends. Networking is very time-consuming but fairly straightforward with platforms like LinkedIn. Secondly, the change in environment takes some getting used to. Demonstrable results, in the business world, are far more appreciated than the innovation behind (or elegance of) a model.
What skills that you developed in graduate school have helped you most in your career?
The skill that I developed in Graduate School that helped me the most in my job is, by far, the ability to derive meaning from real-world data. In a social science like Economics, a lot of effort is put into empirical strategies that derive estimates by trying to circumvent the imperfections of observed data. This, in my mind, is a huge advantage that economists have over mathematicians or computer scientists.
What skills have you had to develop on the job?
There have been many skills that I’ve needed to learn on the job. There are a whole new set of tools that I needed to learn, such as presentation techniques and a few statistical techniques. More importantly, though, I’ve had to learn how to navigate the protocols of the corporate environment.
What advice would you give current GC students who are interested in pursuing a similar career path?
My advice to GC students looking to pursue the same career path is to go for it! More specifically, I have two points to make: 1) Start networking early. Schedule conversations or meetings with everyone you know (and even some people you don’t know) who works in the field. Impress them by being interested and interesting, and then ask them to connect you to someone else they know in their company or industry. Pretty soon, you’ll meet with people who will be sufficiently impressed by you to advocate for you. This is your way in. Don’t waste time sending out a bunch of applications and cover letters—referrals are the way to go. 2) It’s more valuable to appear well-rounded than to play to your strengths. PhD candidates are sometimes seen as naive academics who have no common sense. You will need to justify that you have the mindset of an MBA while still being as smart as a PhD.
Interview with Paul Schweigert, Analytics Consultant, Marketing at IBM
What is your area of study at the Graduate Center?
I’m currently finishing my PhD in History. My specialty was Modern Europe, and my dissertation examines debates in France about the meaning of American democracy in the 1830s and its relevance for France.
What is your current position? What are your job responsibilities?
I work as an Analytics Consultant at IBM in the Performance Marketing department. Current job responsibilities include working directly with source data to analyze and optimize marketing effectiveness across the entire digital marketing funnel; analyzing web site performance, trends, and click streams, including data mining of customer-level web behavior and results of digital marketing initiatives; identifying data-driven digital channel best practices and scaling to all IBM digital marketers through education, communication and analytics services; designing and developing scalable digital optimization capabilities to be rolled out across the IBM business; and directly interacting with IBM marketing teams and executives to scope business requirements, develop analytics solutions, interpret results, present findings and implement recommendations.
What is an average day like for you?
It depends on where we are in a particular project. IBM uses the CRISP-DM process, which includes the following stages: business understanding, data understanding, data preparation, modeling, evaluation, and deployment. So I could find myself meeting with key stakeholders about business needs in the morning, building a series of aggregated data tables in the afternoon, and revising a model’s logic at the end of the day.
How did you transition from graduate study in a humanity/social science into a career in a STEM-oriented industry?
I originally went to school for mathematics and computer science, but when the dot-com bubble burst I decided to go for my PhD in history (where ironically employment prospects were even worse, though I didn’t know it at the time). So I already had a STEM background. After a few years in grad school I came to the realization that academia wasn’t for me, and I began taking steps to return to a career in mathematics. My original plan was to go back to school for a Masters in Applied Mathematics, so I audited a few math and stats classes and worked through my old C/C++ textbooks to get back in a mathematical frame of mind. It was around this point that I saw an announcement for an info-session on internships at IBM Performance Marketing. I applied, got the internship, and at the end of the summer was hired full-time.
What skills did you develop in graduate school that have helped you most in your career?
There’s not really a lot of overlap between my graduate studies and the work I do at IBM. That being said, graduate school was very helpful in developing the kinds of critical thinking skills—such as developing an argument, evaluating evidence/data, and the importance of context—needed in the modern workplace.
What skills have you had to develop on the job?
There are two types of skills I’ve been developing since I started at IBM. The first is gaining proficiency in the tools that we use on a day-to-day basis, such as our data visualization programs, our database programs, and our analytic software. In other words, learning how to apply general analytical skills (for example, determining the correlation between two variables…) in a specific way (…using IBM SPSS Statistics). The other type of skills I’ve developed I would classify as continuing education/career advancement. There are a number of programs at IBM designed to help employees develop new skills and advance/grow their careers. For me, that’s involved taking a few courses to enhance my advanced analytical skills (building models and developing algorithms).
What advice would you give current Graduate Center students interested in pursuing a career path similar to yours?
Learn statistics and programming logic (if these are new to you, there are plenty of free introductory courses available online).