We welcome you to the fourth edition of Ladies of Data! An inclusive event for everyone who is interested in data science & diversity.
In the 2023 version of Ladies of Data, we focus on networks, from a data science perspective but also from a personal perspective. That is why the event will end with drinks, where you can meet, mingle and join discussions around different topics.
If we think of a network, social networks such as Facebook, Twitter or LinkedIn immediately pop into our mind since they are part of everyday life. However, these social networks we use to communicate online with selected groups of people are just one of many types of networks we encounter daily. If we take a train to commute to work, we are taking advantage of the railways’ network; if we make a bank transaction, we are part of a network that connects users to banks; If we buy a product online, we are connecting ourselves to a defined set of preferences about goods that also constitute a network; companies compete with each other in a network since most market offerings are related to multiple other offerings. Data scientists are increasingly aware of how crucial networks are to making sense of the world around us. Almost everything has a relational aspect that can be modeled as a network, and the few things that don’t, are likely still embedded in a network.
Claudia Zucca is an Assistant Professor at the Jheronimus Academy of Data Science, Tilburg University. She holds a Ph.D. from the University of Exeter and previously worked as a post-doctoral researcher at the University of Glasgow. She is also a Marie Curie Alumna. Her research focuses on data analytics, especially network analysis, applied to the social science domain, such as forming political opinions, introducing innovation in organizations, and health policy implementation.
Doreen Posthuma is a senior data scientist at bol.com, the largest e-commerce platform in the Benelux. She obtained her MSc in Econometrics at the University of Groningen. During her academic years, she gained experience in various fields, from writing an article on extreme values in speed skating records to working as a risk analyst in consultancy. She has been working at bol.com for 3.5 years as a data scientist where she has developed her expertise in both the forecasting and fraud domains. She currently works in the Assortment Quality & Product Catalog department at bol.com.
“In this talk, I present how we implemented network analytics to combat fraud at bol.com. I begin with a short introduction about fraud in the online retail industry, before delving into how we started using network analytics @bol.com to detect big fraudsters who use multiple accounts. I will discuss the graph data model that we utilized, how we apply graph queries, and which algorithms can be run on these graphs. By the end of my presentation, you will have a better understanding of how network analytics can be a powerful tool for identifying and preventing fraud in the e-commerce industry.“
Dr. Ksenia Podoynitsyna is an Associate Professor in Data-Driven Entrepreneurship at JADS. She also serves as the Program Director for the master “Data Science in Business and Entrepreneurship” and is the Data Entrepreneurship research unit head at JADS. Her research focuses on the ways data allows to create and capture value through innovative business models, ecosystems, and platforms, and on risk and uncertainty management in new organizations. Ksenia is keen on doing research with clear business and societal implications, such as in Ph.D. projects funded by the EU, EIT KIC InnoEnergy, Philips, CZ, and KPN.
Pommeline is Product Owner of the B2B data team at DPG Media, a leading media group in Belgium and The Netherlands. Her team of data engineers fuels the advertising domains by providing them with the right data for analytics and reporting purposes in a qualitative and cost-effective way. Pommeline already feels right at home at JADS: she started the Professional Education program Data Science for Business Managers last year and is currently working on a case study for her organization.