Research lead at Entis, working on alternative data for quant equity strategies. After finishing her PhD in astrophysics at Leiden university, she worked at Deloitte Innovation, and is currently at Entis, a spin-off from Deloitte and an independent business unit of APG.
Putting data science to work for long-term sustainable investing.
At APG, the largest Dutch pension asset manager, we use data science to address two important needs: making responsible and sustainable investments, and generating excess returns. APG is among investors committed to helping the realization of the United Nations Sustainable Development Goals, and the first use case describes how we identify sustainable development investments (SDIs) among 10000 global companies. The second use case is about quant equity strategies and the use of data science methods on alternative data.
Hospitals collect data all the time. Until now, they are not taking full advantage of the information that is hidden in those data. That information could increase the efficiency of processes and the quality of care. But changing this is not a simple task. Healthcare professionals are not used to registering information in a way that it is easy to search. Also, privacy issues play a role. Interested in how Esther is trying to support the Jeroen Bosch Hospital at its road to data maturity? She will describe her approach and discuss her dilemmas illustrated by some real-life cases.
She studied Business at the University of Amsterdam and has a Master’s degree in Leadership and Management. As manager she’s responsible for one of the six disciplines at Yacht trainees, divided into two teams. We help young and highly educated talents – that just finished their studies – to explore opportunities within their specialty, to build their professional network and we emphasize the importance of hard skill and soft skill development. The three-year program helps our trainees to discover their personal strengths and challenges to ensure they will become resilient and futureproof professionals in an ever changing environment.
Since March 2019 I started the Yacht Data traineeship. During this 3-years traineeship I will focus on my professional as well as my personal development. In January 2019, I finished my Master’s degree in Data Science at Tilburg University. For my Master’s thesis I examined whether personal information (hobbies, interests and personality traits) could predict music preferences by conducting classification and regression analyses in R. Besides working my magic with data, I like to use my soft skills to connect with people. The combination of analytics and communication is what gives me positive energy after a day of working.
How to become a future proof data scientist, by developing your soft skills.In addition to a great set of hard skills, we emphasize the importance of developing your soft skills. For instance, you might be able to program the most advanced scripts, but if you don’t know how to tell your story to a group of stakeholders, it’s hard to make a real difference. In our webinar, we discuss how to develop the full package and how to get the best performance out of your career as a data scientist.
Zeinab is a senior data scientist at TomTom, empowering their products and services using data. She leverages Machine Learning and mathematical modeling to turn data into an insightful story. Her mission is to bridge the gap between data and decision making, fostering a data-driven culture. Next to being a data scientist, she is a mathematician with a passion for solving problems and reasoning with logic. My educational background includes an MSc in Mathematics from the University of Tehran, Iran, and a Ph.D. in Computer Science and Logic from LORIA (Lorraine Research Laboratory in Computer Science and its Applications), France. She became a data scientist to apply a scientific approach to decision-making and use my technical skills to help people make intelligent and better decisions.
Data and AI at TomTom: How We Are Transforming Mobility
TomTom is a location specialist. Everyday we receive a massive amount of data collected from our products in the real world. In this talk, I will show how TomTom is generating insights and products from this data.
Project manager of the Data & Analytics department of the Rabobank. Responsible for the operations of the department which is formed by teams of advanced analytics, applied analytics and business intelligence with a broad portfolio of data- driven products. She has track record as change manager (Master Black Belt Lean) of transformations towards a data driven way of working within multiple industries e.g. Tax, Banking and Non Profit.
Accelerate the Data Driven way of working at Rabobank.
What is the most ideal process to develop data driven products? How to make sure that data driven products have their full impact? How do these innovations change the way of working of the business? All key questions for being successful with data driven innovation and a data driven a way of working. During the webinar, I will share the approach the Rabobank took to transform to a digital bank, pointing out critical success factors and best practices.
Margot was born and raised in the Netherlands. After receiving her MS degree in Applied Mathematics at the University of Delft, she moved to the U.S. in search of hillier and sunnier places. In 1996 Margot received her Ph.D. in Scientific Computing and Computational Mathematics at Stanford University. Before returning to Stanford in 2001, she spent nearly five years in Auckland, New Zealand as a faculty member in the Department of Engineering Science.
Margot is a professor in the Department of Energy Resources Engineering at Stanford, interested in computer simulation and mathematical analysis of engineering processes. From 2010 to 2018, she directed the Institute for Computational and Mathematical Engineering. Since 2015, She’s the Senior Associate Dean for Educational Affairs in the School of Earth, Energy and Environmental Sciences. She specializes in renewable and fossil energy production. Margot is also active in coastal ocean dynamics and yacht design, as well as several areas in computational mathematics including search algorithm design and matrix computations.
Serena is a Data Science Customer Advisor at SAS, based in Tervuren, Belgium. A polyvalent analytics enthusiast and evangelist, her overarching goal is to foster an efficient, productive, healthy, more equitable society. She was initially trained in both electrical engineering and physics, and her graduate work at Stanford focused on the optimization of solar cells. She has since applied her analytical skills to problems in maternal health, global health, and neuroscience, as well as to teaching and developing courses in statistics and machine learning. Currently, she advises clients on the applications of data science and AI using the broad range of SAS tools.\r\nShe is also a singer, art dilettante, and a very proud mother.
Esther is a Data Scientist at Achmea. She likes to combine her theoretical knowledge about Data Science, statistics and business with practical skills such as programming, data processing, visualizing and presenting. She prefers to be involved in an assignment from start to finish, for which Achmea is the perfect environment. She gets a lot of energy from working together with her colleagues. Esther earned a masters degree in Business Analytics at the Vrije Universiteit Amsterdam and worked as a Data Scienist at a consultancy company before she started at Achmea. In her free time, Esther likes to travel. Also, she likes running and recently started playing tennis.
Maaike works as a data scientist at Achmea. She obtained her masters degree in Mathematics at Utrecht University and her PhD in Logistics and Operation Research at the Vrije Universiteit Amsterdam. Together with her colleagues she implements models and analytical tools at Achmea to automate processes and improve the customer experience. She likes to use machine learning to solve business problems such as predictive models for customer value and network analysis to detect fraudulent claims.
The road to data driven insurance. Use cases, opportunities and risks through the eyes of data scientists.
Curious how machine learning models are used at a big insurance company? Data scientists, Maaike and Esther will share their perspective on the role of data and AI at Achmea. They will discuss the challenges they are facing and how to deal with them. Real use cases will be explained such as a network analysis to find fraudulent claims and image recognition to detect solar panels. So do you want to learn more about the road to become a data driven company? Come and join our session!
Watch it back
Putting data science to work for long-term sustainable investing
Senior Data Scientist at Entis APG
A Hospital's road to data maturity
Esther de Vries
Coordinator Data Science at the Jeroen Bosch Hospital
How to become a future proof data scientist, by developing your soft skills
Britt van Ballekom
Data Scientist at Yacht
Data Scientist at Yacht
Data and AI at TomTom: How we are transforming mobility
Senior Data Scientist at TomTom
How to transform an organization into a data driven organization
Irene van der Lugt
Data, AI & Analytics at Rabobank Group
Data Scientist at Rabobank Group
Hurtling down the data highway. The adventures of a Dutchie in Silicon Valley
Professor at Stanford University, Co-Founder & Co-Director @WiDS_worldwide.
Transparency, algorithmic accountability, and model interpretability
Data Science Customer Advisor at SAS,
Data Scientist & Consultant at Pipple
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