Meet a Data Scientist: Frederike Dubeau
WiDS Puget Sound and Data Circles is excited to present the next entry in our series, “Meet a Data Scientist!”
“Meet a Data Scientist” is dedicated to recognizing the amazing women powering the Puget Sound area’s data science community, spotlighting their journey into the field, their incredible accomplishments, and the weighty challenges that they faced along the way. This lies at the heart of WiDS Puget Sound and Data Circles’ mission of inspiring women to enter the data science field by showcasing its many incredible role models.
Do you know any marvelous women in data science? Send us a tip here!
Frederike Dubeau was an NCAA Division I athlete who started her Business career at PACCAR, a Fortune 500 company headquartered in Seattle, Washington. PACCAR partially funded Dubeau’s Master’s Degree in Predictive Analytics, and Dubeau, in turn, applied what she learned directly to PACCAR’s operations, transforming the way the company did business. She helped establish a Data Science Center of Excellence at PACCAR and went on to become a Manager of Data Science at Logic20/20, a business and technology consulting firm where she currently works.
“Communication is the most important part of data science,” says Frederike Dubeau, Manager of Data Science at Logic20/20, a business and technology consulting firm headquartered in Seattle, Washington. “If you’re able to present complicated topics in a clear and concise way to people who have less familiarity, and convey the benefits of a solution, that’s crucial.” Dubeau knows this because her ability to communicate the value of data is a critical driver for her career.
Dubeau started as an intern about 10 years ago in the Purchasing department at PACCAR, a Fortune 500 company and one of the world’s largest manufacturers of medium- and heavy-duty trucks. She had just earned a Bachelor’s Degree in Business Administration with a focus in Supply Chain Management from Cleveland State University in Ohio. While she had played Division I soccer throughout college, a choice that had provided her many valuable experiences, she had not had the opportunity to do internships as an undergraduate and find her professional passion. Fortunately, her bachelor’s program, which was statistics-heavy and focused on topics like demand forecasting, struck a strong chord with Dubeau. The PACCAR internship confirmed that she really wanted to focus her career on data.
Dubeau accepted a full-time job in the Materials department at PACCAR Parts, the aftermarket parts division of PACCAR, in a role that focused on reporting inventory KPIs. In this position, she was happy to work with data, but felt that more could be achieved with the application of data science techniques she had learned about. The challenge was, however, that the 26,000-employee company had no formal experience with data science applications. Fortunately, Dubeau was surrounded by great leaders at PACCAR who gave her opportunities to showcase the power of data to others across the division.
As she looked to further her education, Dubeau remembered one of her undergradutate professors who had started each class with interesting examples from the news of how data and statistics were being utilized to solve a diverse set of tangible, real-world problems. In those moments, she was wowed. “Data!” she’d thought, “Applying those approaches to the real world could be cool!” She chose to get a Master’s Degree in Predictive Analytics from Northwestern University, instead of the more traditional MBA route that many of her cohort took. She studied after her working hours, and PACCAR supported this choice by covering half of her tuition costs.
The investment turned out to be good for both parties because Dubeau pursued topics that inspired her, and then she applied her new knowledge at PACCAR, transforming the way it did business. Dubeau says,
“I was using what I was learning in school in my day-to-day with my team. I was showing there was a different path. Leadership was also seeing the value that data-driven approaches could bring.”
Dubeau at a PACCAR shareholder meeting.
When she graduated with her Master’s Degree in 2017, she looked for other teams who were using predictive analytics at PACCAR. She discovered that PACCAR’s IT Division had a plan to start a data science Center of Excellence (CoE). When she had the chance, Dubeau made the move and joined the four-person CoE team. Initially, the CoE team acted as an internal consulting group, approaching different divisions of the company (which include, among others, Peterbilt, Kenworth, PACCAR Parts, and DAF Trucks) with novel and powerful analytics applications. The team demonstrated that they understood the business side of the problems each division faced and they were able to scope advanced solutions. In those moments, she says,
“Defining the business value was key. That was the main driver for continued investment in the group and growing the team across the organization. With data science, it’s not just Oh great you have a model that can predict x, y, z; it’s also How do you put it into production, or use those insights?”
The team developed insights, put solution after solution into production and grew their team. Within four years, their team of four grew to about thirty people, across multiple divisions. They operated using a hub and spoke model, with their CoE as the hub, and smaller teams in the divisions as the spokes. Team growth was a challenge. “Being a manufacturing company in the Seattle area, competing with big tech firms for analytics talent was tough.” Once again, she relied on her ability to communicate the impact these technologies could have at PACCAR.
“Many times, people with non-traditional backgrounds, who had curiosity and capability, were the ones we were able to convert toward data science roles. A lot of times, for these projects, the business or engineering backgrounds they had or other experience were really helpful.”
As an early member of the CoE during the high growth phase, Dubeau helped establish data science best practices for PACCAR and defined the career paths for the Data Scientists at the company.
About 18 months ago, Dubeau left PACCAR and joined Logic20/20. She is now a manager in the Advanced Analytics practice and delivers data science solutions to a new set of customers.
In her current role, she works with southern California utility companies, helping to prevent electricity outages and wildfires that result from trees coming into contact with power lines. While wildfires are a big problem in California, vegetation management is a problem for utilities across the planet. Dubeau says, “A ton of work goes into managing crews and inspections, trimming vegetation, and follow-up work.” She explores data related to tree growth patterns to help clients understand which areas, at which times of the year, should get prioritized across service territories.
Dubeau on a field visit to project locality, inspecting southern California utility lines
So how does one cultivate the good communication Dubeau sees as essential? She says,
“I’m an athlete. Practice is what I always did, so I promote that, which can be harder now with remote work. One-off conversations, or talks with larger audiences, like presentations to management or at conferences, are all great opportunities,” she says. “It’s always uncomfortable to present. As with anything, by doing it more, you get more comfortable, and you get better.”
She suggests even finding small ways to connect professionally and communicate, like describing your work to colleagues not directly connected to your projects, or talking about your work with other people in your network. She remembers having a manager who said,
“If you can’t explain this to me in a simple way, you probably need to learn more about it.”
While she worries that may come off a bit harsh, she does believe it is true. Dubeau says she has worked with difficult stakeholders in the past.
“The biggest thing is educating [stakeholders] and showing the concepts in a digestible way, but also clearly defining the measures of success for what they are trying to drive forward. If you lay that out first, and show you are doing this because you are moving that metric from a to b, and this is how we will do it. That’s important.”
As a consultant, data scientists can expect projects to be much more defined within a statement of work, but within a larger organization, that may not have established data science methods yet, objectives may not be so clear, and things can get messy.
“Defining the solution, documenting the delivery items, and laying out a road map with clear delivery dates helps projects stay on track. Early in my data science career, I had projects that went on forever because it was not clear what the measurements of success were.”
All of this boils down to practicing and getting good at clear communication.
Another helpful carry-over from her background as a soccer player is that Dubeau sees data science as a team sport.
“You must have collaboration. The data engineers get the data to the right place and in the right form. If data is not accessible or not reliable, the data scientists can’t easily pick it up. The data scientists explore and create the models, and then cloud engineers put the models into production in a scalable way. It is a collaboration, not just with the technical pieces, but also with the business owners. Understanding how to scope a data science project is crucial because there are so many different pieces along the way and it can fail if you don’t have buy-in from the person who owns the process.”
Dubeau stays on top of what’s happening in Data Science by staying up to date with certificates and new technologies. Her recent work focused on GIS data, and so she’s excited about Amazon SageMaker geospatial capabilities. She also sees the projects on which she consults as opportunities to learn more about a variety of industries and the world. For example, in her current role, she’s learned a lot about government regulations on privately owned public utilities in the state of California.
Clearly, her roles have varied dramatically; so how does Dubeau describe data science to people? She says it comes down to using data to understand patterns, being able to process information, and finding ways to optimize current processes “..to do what you’re doing, only better or on a larger scale—to save time and reduce risk.”
When Dubeau is speaking with people that are considering data science as a career, she highlights the many areas on which a person can focus. For example, you can be super technical, with an in-depth understanding of the algorithms and underlying math, or someone (like herself) can understand business needs along with what is possible technically, to bridge the technical and business teams. There are many other flavors of data scientists, though, and Dubeau admits that the infamous imposter syndrome does exist. To that, she says,
“Find the skills you’re good at and lean into those while also staying on top of the technology. For me, I’m an extrovert and I’m curious. I like to talk to people and understand problems, then come back to my team and convert those into technical pieces of work.. and I’ve learned that, on a day-to-day basis, I need that social part!”
And Dubeau has found ways in her data science career to combine her passion for data and for people, to communicate data science’s strengths and solutions, to bring value, and make a difference in the companies where she’s worked and in the communities impacted by them.