There is a growing recognition across organizations of all types that in order to stay competitive, they need to adopt data-driven decision making and operations. At the same time, existing policies, risk frameworks, and corporate culture are often at direct odds with the commitment to transform organizations into data-centric ones: traditional approaches to governance are not well suited to support the fast, agile, and ever-changing world of data science.
Lyudmila Lugovskaya and Stuart Coleman discuss various challenges they have encountered over their professional careers, including technical issues such as data acquisition from numerous and disjoint data sources or modeling without having access to a cloud platform or GitHub, and share their successes. Lyudmila and Stuart also address cultural challenges—especially the skepticism and reluctance that comes with adopting new ways of doing things—and offer tips on how to deal with these issues.
Lyudmila Lugovskaya is a data scientist at Lloyds Bank. Lyudmila has an interdisciplinary background in business, finance, and psychology and works to apply decision and data science to real-world problems and help businesses make better decisions by unlocking the potential of data. Prior to Lloyds Bank, Lyudmila spent a few years in the financial industry, specializing in corporate credit risk with a particular focus on emerging markets, and taught finance to university students. Lyudmila holds a PhD from the University of Cambridge, where her doctoral research was devoted to predicting the default of small and medium-size enterprises on the basis of financial and nonfinancial variables, as well as an MSc in psychology.
Stuart Coleman is a data scientist at Lloyds Banking Group working in fraud prevention. Stuart has seven years of experience working as a data scientist in both the finance and startup spaces. Previously, he was a data scientist at Growth Intelligence, a predictive marketing company; the founder of a startup delivering personalized learning for high school students; a quantitative analyst at UBS, where he modeled the equity derivatives market; and a research fellow at Imperial College working in turbulent flows. Stuart holds a PhD in fluid flow in complicated geometries from Imperial College.
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