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Alumni Profiles Series: Randi Griffin
Randi Griffin received her B.A. in Human Evolutionary Biology from Harvard University and her Ph.D. in Evolutionary Anthropology from Duke University, where she focused on the intricacies of primate evolution. During her doctoral program, she competed in the 2018 Winter Olympics. After completing her Ph.D. in 2018, Randi pursued a career in data science, leveraging her strong analytical foundation and communication skills. She has worked as a Marketing Data Scientist at KAYAK and taught analytics courses as a lecturer at Northeastern University. Now, she is a Senior Data Scientist at Boston Consulting Group, where she continues to apply her knowledge and expertise to solve complex problems for organizations.
What initially sparked your interest in evolutionary biology and anthropology?
I've been interested in evolutionary biology since I was a kid, actually. It's a little ironic because I grew up in a community that mostly didn't believe in evolution, but I found the controversy surrounding it really enticing. I felt like I had to get to the bottom of it and come to my own conclusions. So, I started studying evolution in school and realized it was actually pretty cool. It's a theory that connects all the diversity we see on Earth with one simple idea.
When I was in college, I met Professor Charles Nunn, who ended up being a great mentor for me. He asked if I wanted to join his lab to try a research project, and we hit it off. He ended up becoming my Ph.D. advisor at Duke later. We worked together for almost a decade, and that's how I ended up in the Ph.D. program at Duke. My doctoral research was focused on the evolution of the skull. The project involved looking at CT scans of skulls from different monkeys, apes, and lemurs, and fitting models to them to understand what drives the evolution of skull shape.
How did your Ph.D. prepare you for a career in data science and analytics?
During my training, I discovered that a significant portion of my research is fundamentally rooted in data science. It's crucial to have coding skills, be able to manipulate data, and understand different types of models to succeed in this field. So, my research essentially became my training as a data scientist.
Since transitioning into industry data science, I've found that people come from all sorts of backgrounds in this field. It's pretty common for people to have a Ph.D., even in topics outside of data science. In fact, I often find that the best data scientists are people who started out in research because they're motivated by questions. They notice a problem or something that we don't understand and start looking for how to solve it, picking up the tools they need along the way. There's a mindset of picking up whatever tool you need to answer the question you have, and everything starts with a question.
What is the most challenging aspect of your job?
For me, working as a data science consultant, the hardest part of the job is often understanding what the client's problem is and figuring out what solution will help them solve it. Clients may not have much experience working with advanced analytics, or they may have poorly defined processes guiding their work. They may come to us asking for a model, for example, without thinking through how it will be incorporated into their workflows and what challenges might arise if the model is wrong. Sometimes, what they actually need is a dashboard or something different than what they're asking for.
So, the biggest challenge is working with the client to really understand what they need, so as to ensure that we don't build something that ends up being useless. Conversely, the most rewarding thing is when we build something that the client comes back to us and says, "This is exactly what I needed." Knowing that we've met the client's needs and delivered something that helps them make better decisions or work more efficiently is extremely rewarding for me.
What other skills have you found to be important for your career?
Communication skills are probably the other big dimension that I would mention as particularly valuable when working in industry. For me personally, I got a decent amount of practice as a Ph.D. student through teaching. That was probably the situation where I had the most opportunity to interact with people and practice speaking to a room, answering questions live, and thinking on my feet. Conference presentations were another opportunity to practice public speaking, but those only happened once or twice a year for me, which is probably typical for many Ph.D. students.
What advice would you give to current graduate students?
For Ph.D. students who are potentially interested in stepping outside of academia, I think investing time into side projects is really valuable. It's probably more common now for people to end up doing very different things after their Ph.D. I think when you're making the jump from academia into industry, something that people like to see is that you have a diversity of interests and skill sets, and that you've taken the initiative to do some projects that are not just ending with a paper or a presentation, but where you actually built a tool. Maybe you built a personal website, or you built an app or a dashboard, something that is displaying data that is interesting to you, answering questions that are important to you, and basically showing a breadth of skill, and also just the initiative to come up with a project that inspires you. For me, those experiences taught me many valuable skills. Additionally, when I began attending job interviews, it offered interesting topics to discuss with interviewers.
Author
Yudong Sun
Ph.D. student, Biochemistry
Yudong Sun is a Ph.D. candidate in Biochemistry. He is interested in the interplay between dietary nutrients and cellular metabolism and how it might ultimately influence physiology. Yudong studied at the University of Wisconsin-Madison, where he received a B.S. in Computer Sciences and Molecular Biology. A curious human being who is still not sure about his professional path, he is constantly learning and exploring.