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Registration & breakfast


Registration & breakfast

Chair's opening remarks

Teri Kurtz Regional Vice President Midwest Platform Solutions Group SAP

Making Data Useful

Despite the rise of data engineering and data science functions in today's corporations, leaders report difficulty in extracting value from data. Many organizations aren’t aware that they have a blindspot with respect to their lack of data effectiveness and
hiring experts doesn’t seem to help. What can be done about it? This session provides a series of actionable ideas aimed at making data and data scientists more useful for business impact.

Cassie Kozyrkov Chief Decision Scientist Google

Making Data Work: Turning Businesses into Intelligent Enterprises

As technologies such as artificial intelligence and machine learning become mainstream, SAP has a new mission – to help turn our customers’ businesses into intelligent enterprises to achieve desired outcomes faster, more efficiently and with less risk. Join and learn how SAP itself embraces this challenge of leveraging data to drive innovation and create new customer value while always respecting privacy.

Justin Litz Head of Business Partner Center of Excellence SAP

Putting the Science in Data Science

Data science techniques have become not just very popular, but also extremely easy to use, thanks to many programming packages that allow users to build and deploy machine learning/data mining algorithms in a few lines of code. In this talk, I argue that it is of vital importance to follow the scientific method when doing data science: be intuition-driven, formulate and test hypotheses, and build reproducible insights. I use examples from my own Astrophysics research to show that the most significant improvements may come from tailoring the choice of features, methods, and evaluation metrics to the specific problem at hand, rather than from using the most “fashionable” algorithms or employing bigger computational resources. This approach has the added value of building understanding of the problem, which serves as a foundation for scaling, optimizing, and generalizing data science solutions.

Viviana Acquaviva Astrophysicist & Data Scientist New York City College of Technology

Networking coffee break

Panel: Creating a Data Culture Within Your Organization

When you create a data-driven culture, teams are more apt to seek out data to help fine-tune strategies and objectives and can take a more active role in measurement and analysis. But cultivating such a company culture is an obstacle for many companies, particularly those that are just beginning to incorporate data throughout business processes and strategy. This panel will explore ways in how consistently drive a culture of data across your teams.

Bharti Rai VP Commercial Effectiveness Novartis
Alaa Moussawi Chief Data Scientist New York City Council
Deepna Devkar VP, Head of Data Science Dotdash
Madhavi Ramakrishna VP Enterprise Data Sciences & Analytics CBS Corporation
Hugo Bowne-Anderson Data Scientist DataCamp
Scott Breitenother Former VP Data & Analytics Casper

The Mindset for Innovation with Data Science: Emerging Technologies and Principles to Nurture a Healthy Data Science Function

As organizations turn to digital transformation strategies, they are also increasingly forming teams around the function of Data Science. Data Science is a combination of skills in mathematics, programming and communication with the application of the scientific method to specific domains of knowledge. But what does it really mean to be a “data-driven” organization? This implies embedding Data Science teams to fully engage with the business and adapting the operational backbone of the company (techniques, processes, infrastructures, culture).
In this talk, Francesca will present an overview of the latest methods and technologies to assess whether your organization is data-driven. You will learn how to nurture a healthy Data Science function within your company, from data generation and acquisition to model deployment and management.

Francesca Lazzeri AI & Machine Learning Scientist Microsoft

Networking lunch

Collecting Qualitative/Subjective Data

Block or charge? Illegal or marginal contact? Important? Observable? Before worrying about the right analyses, the most fundamental issue is ensuring the integrity of data collected, which is only made more complicated when dealing with questions of judgment. This session provides a look at how the NBA tries to overcome this when rating the thousands of referee decisions make each game with a rigorous data collection program and propriety software system.

Steven Angel Senior Vice President of Basketball Strategy and Analytics NBA

Making Data a Strategic Asset

Incorporating data into your business strategy can be a confusing and complicated task. I will review a few examples of how to leverage your marketing and web traffic data into to easy to consume dashboards to help stakeholders inside and outside the organization.

Amanda Yang Director of Data, Analytics & Technology New York Magazine

Leveraging Communications Data to Improve Business Results

Communications data provides an opportunity to assess how a company presents itself external and internal directly affects business results. There is an overwhelming amount tools and metrics to measure an organizations communications which can make knowing where to start confusing. This presentation will go through the basics of communications data and demonstrate its value through real life examples. The case studies will examine how a company can leverage its communications output to increase patients to a hospital, drive leads for its newest car model, and impact its stock price.

Orin Puniello Research Director, Predictive Analytics Ketchum

Networking coffee break

Fireside Chat: Data Science Challenges in Behavioral Health Care Analysis

While the use of AI and ML in healthcare has become standard practice these days, their application to behavioral health presents some unique challenges. In this chat, I’ll discuss some of the ways Talkspace is leveraging data science to better understand and improve the process of “talk” therapy, including ensuring an optimal client-therapist match, learning optimal treatment ‘protocols’ in the absence of explicit interventions, and determining client progress.

Bonnie Ray VP Data Science Talkspace

Building Analytics System to Improve Your Prices and Profits

Setting the prices for the products or services is the most critical decision in a firm, in particular, for the products which are perishable such as hotel rooms, show tickets or seasonal goods. What makes a customer to buy a product or to choose one product over the others? How should prices to be adjusted over time based on seasonal factors and the observed demand to date for each product? Pricing Analytics is using historical price and demand data to determine the best price of a product for the future sales to maximize revenue or profits, by analyzing the trade-off among prices, costs, and customer response. For perishable products, building an analytics system to dynamically adjust the prices is the key to success, the goal is to provide the right price for each product for the right customer segment through right channel at the right time.

Dasong Cao Principal Data Scientist Wyndham Destinations

Chair's closing remarks

Teri Kurtz Regional Vice President Midwest Platform Solutions Group SAP

Networking drinks reception

Networking drinks reception ends at 6.00pm.

Registration & breakfast


Registration & breakfast

Chair's opening remarks

How AI Forced us to Rethink our Data Governance

Adam Petranovich Principal Data Scientist Prognos

How World-Class Companies Are Using Data to Create an Unforgettable Customer Experience

David Norton orchestrated the initiatives that made Harrah’s/Caesars Entertainment one of the greatest marketing companies in the world. His approach of using data to identify opportunities for the business, developing the narrative to sell throughout the organization and partnering with various constituents to drive successful implementation operationally is unparalleled. In The High Roller Experience, he shares his secrets to creating an unbeatable marketing strategy. In addition to discussing core items such as analytics, CRM and loyalty programs, he examines the leadership and organizational processes required to create a customer-centric and data informed business.

David Norton Author The High Roller Experience

Building Data Science: Transitioning Companies to Data Driven Methodologies

Scott Sokoloff, Chief Data at Newsela, shares his experiences and insights in how to create a data driven culture. Told through a lens of use cases and personal insights; Sokoloff, engages with the audience to tailor this keynote to the specific questions of those in attendance. Key takeaways from the session are “Know Your Business Objectives,” “Invest in Internal Resources” “Build the Infrastructure for Success” Audience involvement is encouraged and everyone is asked to bring any use case or practical concerns they may have in transitioning their company towards a data driven culture.

Scott Sokoloff Chief Data Officer Newsela

Networking coffee break

The Faces Behind the Data Points: Auditing Black Box AI Services

My topic goes into the auditing process of black-box AI services, and how this process fits into a data product development life cycle. I will speak on the results of one such audit I conducted of a computer vision / facial analysis tool I was evaluating for use in processing photos for feature extraction. Touching on the theme of algorithmic bias, these kinds of audits can help protect the quality of data products, ensuring that products work for customers of all demographics, as opposed to failing more often on particular customer segments. To learn more, I’ve written an article about how Viacom approaches these issues:

Diana Saafi Sr. Data Scientist Viacom

Insight to Action: Simplifying the Analytics Process to Improve the Speed of Decision-Making

Integrate analytics into everything you do so that you can lead decisions with data and information. Learn to implement a scalable analytics infrastructure where the right questions can not only be asked, but more importantly answered with insights and recommendations. With the right people, operating model and analytics process in place, the speed at which the organization can utilize information can rapidly increase, leading to signficant improvements in performance.

Dan Shin COO Cadilus Inc.

Cracking the mystery of the Buybox on Amazon: A Journey that lead to 40X growth in less than two and a half years.

In this session I will tell the story of my wing of business on selling on Amazon – the multifaceted challenges, and solutions that I’ve implemented along the way. A fascinating cross-breed between Game Theory and Data Science. Winning the buybox strategy and creating the dynamic repricer to optimize profit and steering clear of various “fraud” like strategies of competition to bring success home.

Boris Kerzhner Chief Data Scientist BookXchange

Networking lunch

Panel: Adapting Using Analytics to the Changing Landscape of Data

This panel will explore how data is changing, and how traditional means of exploring datasets need to be evaluated in keeping with the innovative analytical tools at our disposal. Items on the agenda include Natural Language Processing, Machine Learning, Qualitative Inquiry and People Research in my talk.

Edwin Chin Chief Data Officer Sweeten
Jeeyoon Park Director of Data Science Walt Disney Company
Jennifer Shin Adjunct Professor New York University
Sumanth Swaminathan Chief Data Scientist Revon Systems

Data Science in the Age of Digital Marketing

When talk about Marketing, the first thing popping into peoples’ minds may be Mad Men, instead of a bunch of nerds hunching over their computers. However, today’s marketing landscape has long been shifting towards digital marketing, and with its rise, Data Science has also been playing an increasingly important role. In this session, I’ll share my experience of building a data science team which help scaling up our digital marketing budget by 10x, our successes and failures, and the learning from it all.

Hao Tong Sr. Data Scientist Tilting Point

How to Formulate and Implement Strategies to Leverage Data Assets

We measure and built grit by gathering, analyzing, synthesizing, and presenting data.

But we realized that we might not be fully realizing the value of this treasure trove of data.

Coming up with the criteria for the right strategy was easy: Be consistent with our vision; Respect privacy rights; and as a non-profit, Generate sufficient revenue to offset cost.

In this talk, I’ll discuss ways to further evaluate and implement successful strategies that leverage data beyond the ostensible.

Larry Shiller Chief Data Officer Rising Stars Foundation

Departing coffee & snacks