Danielle Dean, Ph.D., is a graduate of our Quantitative Psychology program in the Department of Psychology and Neuroscience. She is now the Principal Data Scientist Lead at Microsoft. Danielle was also recently honored with the 2017 Distinguished Young Alumni Award from UMass Amherst.
Working in the Artificial Intelligence and Research Organization, Danielle leads an international team of data scientists and engineers in building predictive analytics and machine learning solutions for external companies utilizing Microsoft’s cloud analytics products. Her twelve-person team is from eight different countries and is cross-disciplinary in terms of the team members’ backgrounds, such as physics, oceanography, computer science, statistics, and medical imaging.
Microsoft is building a lot of artificial intelligence and predictive analytics solutions, which can be leveraged through the cloud Azure platform and products such as SQL R services. Danielle works with customers building out analytics solutions, which often compromise of open-source data analytics and machine learning solutions that leverage the cloud computing infrastructure of Microsoft’s Azure platform. Then, she uses that work to make sure that Microsoft’s products can solve real business problems and gathers feedback through the direct use of the products for the teams building them. Danielle says, “It’s a really fun role because I both get to build custom analytics solutions with customers, and then also work with the product teams to make sure those products are improved over time so that as we move forward we can continue solving bigger and even greater problems.”
Danielle and her team also build out samples, templates, and write blogs (check an example out here!) and publicize their work at conferences. She works with companies to do predictive maintenance and quality assurance. By trying to understand and utilize all data, such as sensor readings, they can better understand when something may fail in the future or how to proactively address issues in the manufacturing process.
Danielle decided to pursue Quantitative Psychology as a Ph.D. student because she was intrigued by how mathematics and statistics can be used to study individual behavior on a large scale to find patterns and frameworks through data. Under the guidance of her faculty advisor, Dr. Dan Bauer, Danielle learned how to think about data from measurement, analysis, to visualization and some of the technologies, programming languages, and tools that enable this.
She says, “One of the most important traits of a data scientist is curiosity – always trying to understand how things work, how to examine data, and how to model different phenomenon. The training at UNC allowed me to nurture this curiosity, learning appropriate ways to structure problems and find solutions using data and models, as well as how to critically think about the use of data and models.” At Microsoft, Danielle shares that she loves the challenging nature of the work and the continuous change in the technology sector. She explains, “For example, I’m currently learning about the applications of deep learning for image classification and it’s incredible to see the continuous progress in the use of data along with increasing computing power to solve incredible real world problems.”
To students considering a Ph.D. at Carolina, Danielle advises: “Learn to work with many different types of people who have different interests and passions and come from different backgrounds than you, as they will give you unique perspectives and help you find who you want to become as a person. Never strive to be exactly like someone else but rather find what drives you and seek opportunities to push yourself.”