Breeding Data Scientists

Data Science, Sutton Center / Sutton South (NY Hilton)
Average rating: ***..
(3.71, 7 ratings)

A true data scientist has a combination of computer engineering ability, mathematical and statistical knowledge, an insatiable curiosity and an understanding of what will be interesting and useful. It is believed that we will have a significant deficit of these specialists in the very near future. So as select schools work toward putting together material to provide future students with the right balance of engineering, mathematical and cultural studies, how do you begin to breed data scientists from the talent already in the market?

Amy O’Connor leads Nokia’s growing centralized Analytics team. Her unique combination of engineering, business and marketing experience made her the perfect candidate to start and build this team. When she took the job 2 years ago, she found herself querying her daughter Danielle frequently. At the time, Danielle was just finishing her undergraduate studies, majoring in Psychology and in Organizational Behavior through Statistical Analysis, as well as minoring in Mathematics/Statistics. Over the past two years, Nokia has further defined its Analytical ecosystem, began to amass a centralized data asset and is increasingly using the data to manage and innovate its business and offerings. Throughout this journey, Amy has had to find individuals who have some of the attributes to become data scientists and provide them with additional training, mentorship and experiences to round out their abilities. One of her newest interns in the insights department happens to be her daughter, Danielle, who is now working toward her Doctorate in Quantitative Psychology at UNC Chapel Hill. Together, Amy and Danielle will share what makes a great data scientist, their different paths to acquiring skill sets and finally Amy will discuss how to spot, attract and train emerging data scientists in what is surely to become a heated market.

Photo of Amy OConnor

Amy OConnor


Amy is a business and technical executive with extensive experience driving growth and change. Amy leads Nokia’s Analytics team and is committed to enabling Nokia to be a data-driven business, ultimately delivering the best experience for consumers. Her charter includes the development of Nokia’s analytics platform, developing and managing Nokia’s data asset, and leading a team of data scientists to deliver descriptive and predictive insights. Prior to joining Nokia, Amy was vice president of services marketing for Sun Microsystems.

Photo of Danielle Dean

Danielle Dean


Danielle is currently a Data Scientist at Nokia, and a doctoral student in Quantitative Psychology at the University of North Carolina at Chapel Hill. Danielle enjoys working to advance and apply statistical methods to address complex business questions, especially using random effects models and mixture models. Danielle is specifically interested in studying issues that arise when modeling developmental phenomenon over time and in the integration of different modeling frameworks. At Nokia, she teams with other data scientists in Nokia’s Insights group to deliver descriptive and predictive insights into Nokia’s new centralized data asset and into business analytic projects and to deliver visualizations of the data and their predictions.


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