June 12, 2019

222 W Merchandise Mart Plaza

12th Floor (#1212)

1871 Offices, Room 2.03
Chicago, IL 60654


Learn how to make everyone more productive with data, from advanced practitioners to business users.

If data is only useful to highly-skilled data practitioners, it’s not living up to its original promise of making your organization smarter, faster, and more effective. Let’s fix that, together.

Join other executives like you for an afternoon of discussions on best practices, use cases, and cutting-edge tools around data practices. Learn from leaders in data who have engineered organizational change or implemented data practices at scale in an afternoon of presentations, and engage face-to-face with your peers at an evening reception.

RSVP today as spaces are limited. We look forward to seeing you!



data.world is the modern catalog for data and analysis. Choose data.world to wake up the hidden data workforce within your enterprise, multiply your data’s value, and create a data-driven culture faster. Bring together employees of all roles, backgrounds, and skills to work collaboratively using the tools they already love. data.world uses a knowledge graph to keep data connected to everything people need to find, understand, and use it. As a result, your data, analysis, and expertise become more discoverable, trustworthy, and reusable. Visit data.world to learn more.


12:30 pm – 1:30 PM



1:30 pm – 2:00 PM

Cars.com’s data science journey

This talk aims to distill the journey of Cars.com’s Data Science team. The application of machine learning (ML) is one of the biggest ‘product and tech’ success stories at Cars.com. This success is measured in terms of incremental gains across multiple business KPIs. Presently, the ML Product influences more than 80% of the revenue and this has been achieved over the course of one year. In addition to sharing the data science journey of Cars.com, this talk will also provide insight about the team structure, the team’s position in a wider tech-product-business organization and introduction to some of the core ML products built so far. Together these areas address current business needs and also shape the Cars.com’s vision for the future.

Speaker Bio

Addhyan leads data science for Cars.com’s applied Machine Learning (ML) efforts. It involves using ML to build state-of-the-art AI technologies that power variety of products across Cars.com. The data science team at Cars has built products to improve search, browse and discovery experience of cars shoppers, and to optimize sales-pipeline and marketing efforts. He previously served as Lead Data Scientist at Groupon Inc., where his focus was on applying predictive models for analyzing and affecting customer behavior, supply optimizations, and personalization. Before this, he held Research Analyst position at Global Analytics India Pvt. Ltd. where he was part of a team building a generic predictive modeling platform in the sector of short-term loans. Pandey holds a Bachelors in Electronics and Communications Engineering from IIIT-Hyderabad, India. Pandey has co-authored 3 scientific papers and is the co-inventor of 6 patents. He strongly believes in interdisciplinary approach to data science.

Addhyan Pandey

Principal Data Scientist


2:05 pm – 2:35 PM

Will you be better off in a “Smart City”?

Technology and data has begun to be embedded in the fundamental structure and processes of the cities and states in which we live. Smart cities are looking to incorporate data and technology that improve the quality of life for their residents and help governments be more efficient. But what does that mean and how can it be meaningful to you? We’ll explore practical, real-life ways that data science, internet of things (IoT), and open data are being used to help cities become more livable and modern that range from predictive analytics, API feeds of real-time public data, and connected sensors to provide block-by-block insights. More importantly, we’ll discuss how it matters to residents and visitors to the city.

Speaker Bio

Tom Schenk Jr. is a researcher and author on applying technology, data, and analytics to make better decisions. He’s currently the director of analytics at KPMG where he leads the smart city and government analytics practice. He’s authored several publications, including a book on data visualization, book chapters on education research, and academic articles on a variety of subjects. Tom has previously served as Chief Data Officer for the City of Chicago, led education research for the State of Iowa, and has held a variety of positions within academia. Tom is the co-founder of the Civic Analytics Network at Harvard University’s Ash Center for Democratic Governance and Innovation. He is also the current co-organizer of the Chicago Data Visualization Group. His work has been featured in The Economist and Wall Street Journal while he’s been featured in television programs on PBS NewsHour and National Geographic Channel.

Tom Schenk Jr

Former Chief Data Officer

City of Chicago

2:35 pm – 3:05 PM

Coffee Break

3:05 Pm – 3:35 PM

Building an Innersource Culture for Data Analysis

While every data analysis produces unique insights, the analysis process consists of many standard processes and building blocks. This talk explores what data analysts in an organization can learn from open source to collaboratively create a reproducible analytical infrastructure. Based on lessons learned at Capital One, we will discuss the motivations for cultivating an innersource culture, practical advice on designing and developing internal analytical tools, and strategies for helping data analysts evolve from passive users to active contributors.

Speaker Bio

Emily Riederer is an Analytics Manager at Capital One where she focuses on building opinionated data products to promote scalable and reproducible business analysis. At Capital One, she has worked across acquisitions and CRM credit strategy and led consulting initiatives for retail partners.

Outside of work, Emily is an active member of the #rstats community. Most recently, she has reviewed packages for rOpenSci and helped to co-organizer the first Chicago R unconference and the inaugural satRday Chicago conference.

Previously, Emily earned degrees Mathematics and Statistics / OR at the University of North Carolina at Chapel Hill. During her studies, she focused on healthcare analytics as a research assistant in emergency department discrete event simulation and a student consultant for a large managed healthcare provider.

Emily Riederer

Business Analytics Manager

Capital One

3:40 pm – 4:10 PM

The Care and Feeding of Data Scientists

Data scientists are hard to hire. But too often, companies struggle to find the right talent only to make avoidable mistakes that cause their best data scientists to leave. From organizational structure and leadership considerations to tooling and infrastructure to avoiding FOMO through continuing education, I’ll share concrete (and inexpensive) tips for keeping your data scientists engaged, productive, and performing their best for your business.

Speaker Bio

Michelangelo D’Agostino is the Vice President of Data Science and Engineering at ShopRunner. As a reformed particle physicist turned data scientist, Michelangelo loves mungeable datasets, machine learning, and long walks on the beach (with a floppy hat, plenty of sunscreen, and a laptop). Prior to his current role, Michelangelo came from Civis Analytics, where he led a team that developed statistical models and wrote software to help companies and nonprofits leverage their data. Before that, he was a senior analyst in digital analytics with the 2012 Obama re-election campaign. He helped to optimize the campaign’s email fundraising juggernaut and analyzed social media data.

Michelangelo has been a mentor with the Data Science for Social Good Fellowship. He holds a PhD in particle astrophysics from UC Berkeley and got his start in analytics sifting through neutrino data from the IceCube experiment. Accordingly, he spent two glorious months at the South Pole, where he slept in a tent salvaged from the Korean War and enjoyed the twice-weekly shower rationing. He’s also written about science and technology for the Economist.

Michelangelo D'Agostino

VP Data Science



4:15 PM – 5:00 PM

Data Literacy Panel Discussion

* Patrick McGarry, data.world (moderator)

* Ali Vanderveld, ShopRunner

* Tom Schenk Jr, KPMG

* Kerstin Frailey, Metis


5:00 PM – 6:00 PM




June 12, 2019
12:30pm – 6:00pm


1871 Building
222 W Merchandise Mart Plaza
Chicago, IL 60654, USA

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