November 6 - 7, 2019

DATAx NEW YORK

Unlock the power of data science to make a real world impact

NOVEMBER 6-7 | NEW YORK CITY

DATAx New York is a cross-industry event for business leaders, strategists, and practitioners looking for best practices and strategic insights to help increase business growth and gain marketplace advantage.

DATAx provides a unique blend of data-focused content tailored to help you find real-world solutions to common challenges.

Our program is specifically curated to examine the most relevant topics on the minds of data scientists and business decision-makers. With an emphasis on collaboration, DATAx is the event where the technical and strategic conversations that change business models are started.

2 DAYS | 4 TRACKS | DATAX LABS | UNLIMITED NETWORKING

EARLY BIRD TICKETS EXPIRE IN:

Speakers

Data Is The Commodity of the Future

Data has become the commodity of the future and the insights garnered from it are revolutionizing the business landscape and changing the way companies do business.

DATAx will be a unique interactive learning and networking experience, providing actionable takeaways to empower you to improve current processes and solutions and thoughtfully integrate new ones. Building a smarter, stronger, and more powerful tech-backed business model starts here.

The agenda is specifically curated to examine the most relevant topics on the minds of data scientists and business decision-makers, with an emphasis on collaboration and knowledge share.

Insights

Bring back actionable insight by participating in two days of candid talks and round tables.

Collaborate with peers in the interactive DATAx Labs. Choose from a series of workshops to fit your business needs and personal goals.

Collaboration

Connect with over 400+ data leaders across all industries and experience levels to expand your network.

Meet the disruptive startups and innovators who are changing the world.

Solutions

Discover cutting-edge tools and techniques.

Immerse yourself in automation, data, and mobile technologies that will unleash your potential.

Stages

Every DATAx stage focuses on how to effectively use data to power business decisions. DATAx provides you with both the strategy and hands-on techniques that can be immediately implemented companywide and across industries.

DAY 1

STAGE 1 – DATA STRATEGY: DRIVING INSIGHTS AND RESULTS

The Data Strategy stage is an immersive thought leadership insights-driven program that fuses together data science and “real world” business strategies.

Designed for Chief Data and Analytics Officers and data champions, these thought-provoking sessions are curated to provide an executive overview of the changing data landscape.

Executives will discover how to effectively leverage data to drive business results.

STAGE 2 – AI/ML TECHNIQUES AND APPLICATIONS

Technical innovation is at heart of DATAx New York.

Join us for the AI/ML: Techniques and Applications stage as we bring together a cross-industry mix of technical leaders and practitioners who are well-versed in Artificial Intelligence and Machine Learning innovation. Discover how their techniques and applications are revolutionizing the way companies use data.

Through real-world case studies you’ll see first-hand how the world’s most innovative brands are using AI and ML to drive business growth and gain marketplace advantage.

DAY 2

STAGE 1 – DATA INSIGHTS: MARKETING AND CUSTOMER ANALYTICS

The Marketing & Customer Analytics stage brings together forward-thinking data and analytics professionals, marketers and product managers for a concentrated program that uses analytics to garner insights that inform key business decisions.

Learn how today’s bleeding-edge companies and innovative experts are using data to build trust and deliver a customized user experience.

Decode the needs of the customer with case studies on how analytics can help to better acquire users, personalize their experiences and build new innovative customer journeys that minimize your company costs and boost your revenue.

STAGE 2 – APPLICATIONS: BUILDING THE DATA PLATFORM

The Building the Data Platform stage provides data scientists with an inside-look at how data-driven companies are creating personalized tools to solve internal challenges.

See technical demonstrations of application and data models and learn how teams have effectively gained internal support and funding for these projects.

Agenda

Day 1 Wednesday 6th

 

0800

0900

1000

1100

1200

1300

1400

1500

1600

1700

1800

Starting at 8am

8am

Breakfast

8:45am

Introduction & Opening Remarks

Starting at 9am

9am

The Gamification of Retail

9:30am

General Session

Starting at 10am

10am

Roundtable Sessions

10:30am

Power Networking Break

Starting at 11am

11am

Fueled by Data and Exponential Technologies: The Cognitive Enterprise – STAGE 1

Getting value out of your data is more important now than ever before. The digital era requires you to react in real time with model-based tools on an enriched and structured data environment. As the business need for data insights increases — particularly as we witness the rise and proliferation of the Cognitive Enterprise — many organizations are using their curated data to power new intelligent workflows and harnessing the power of data with AI and other exponential technologies. You will hear multiple case studies from our client successes and better understand how enterprises like yours are realizing the ‘inside-out’ potential of data-driven outcomes exploited through these exponential technologies at scale.

Bruce Tyler Cognitive Process Transformation and Data Leader
IBM

11am

Going Beyond Big Data: Taking ML to the Next Level – STAGE 2

All retailers want to know their target buyer, but understanding the past and present of their interactions simply isn’t enough, predictive analytics is the next step; • How ML can enable price optimization, product placement and assortment selection • Using machine learning algorithms affectively for generating suggestions for substitute and complimentary items • Utilizing optimization algorithms to reduce store cost by optimizing replenishment cycle and safety stock • Scaling algorithms to generate recommendation for individual stores and monitor their performance

Hamza Farooq Principal Data Scientist
Walmart

11:30am

Designing a Data Science Center of Excellence – STAGE 1

Organizational leaders are being bombarded with AI and all the hype that goes with it. Many are throwing their hands up out of frustration while others are chasing the wrong projects, wasting time, money and opportunity. The best solution for most organizations is to find someone on the inside with the knowledge and network and arm them with a data science center of excellence. In this session, we will share the journey we’ve undertaken at Mount Sinai to create our own DISCO floor, what types of services can we offer on a shoe string budget and how we can quickly deliver value to the business where they need it most – preparing the culture for change.

Michael Berger VP, Chief Data & Analytics Officer
Mount Sinai Health

11:30am

TBD Session – STAGE 2

Starting at 12pm

12pm

TBD Session – STAGE 1

12pm

How New York Times is Transforming the Business With Machine Learning – STAGE 2

Advertisers tend to focus on finding a given type of person (based on third party data) and targeting them wherever they can find them. We argue that targeting them based on what they are reading and reacting to in the moment can be far more accurate and performative. Over the past two years, NYT has created award-winning ML-based contextual targeting methodologies that take our best asset (our content) and use what we know about it to redefine targeting in a way that’s safe and accurate

Kendell Timmers VP, Advertising Analytics
The New York Times

12:30pm

Overcoming Organizational Challenges in Data Science – STAGE 1

Designing an efficient data science team in a business is often complex. There are many decisions and tradeoffs and resources are limited. This session will seek to lay out possible organizational design considerations and some learnings from implementing data science teams, strategy for developing a data science capability and how Plated integrates data science and business strategic planning. Last, this talk will explore multiple tools, frameworks and techniques outside of a data scientist’s core model creation skill set that allows them to navigate and have a larger impact in a business setting.

Daniel Gremmell VP, Data Science
Plated

12:30pm

Healthcare Panel – STAGE 2

Ernie Ostic SVP of Products
MANTA

12:30pm

TBD Session – STAGE 2

Starting at 1pm

1pm

Lunch

Starting at 2pm

2pm

A History of Making Data Science: AIG, AMAZON, ALBERTSONS – STAGE 1

Developing an internal data science capability requires a cultural shift, a strategic mapping process that aligns with business objectives, a technical infrastructure that can host new processes, and team capability to alter business practices that create measurable efficacy. Join us to learn how to build opportunity maps that lead to hiring plans and infrastructure specification.

Haftan Eckholdt Chief Data Officer & Chief Science Officer
Understood.org

2pm

TBD Session – STAGE 2

2:30pm

TBD Session – STAGE 1

2:30pm

Applying Practical Data Science – STAGE 2

Applying machine learning in a business context isn’t always straightforward – you must often trade exactness for actionable results. In this talk, we’ll discuss practical considerations involved in model building and deployment. Grasp an understanding of when to be flexible with assumptions, when it’s appropriate to deviate from the textbook, the importance of empathizing with your stakeholders, and leveraging your team to deliver optimal results. Discover actionable learnings that can be applied across many industries in any business size, from start-up to large corporations.

Ilan Man Head of Data
Trialspark

Starting at 3pm

3pm

Panel: Using the Power of Data to Drive Business Growth – STAGE 1

Sit in on this thought-provoking discussion focused on the use of data analytics to inform the business and increase revenue. In today’s market place companies must find ways to disrupt themselves or create tools that will help them gain marketplace advantage. Learn how businesses are using data science to build new product offerings, improve service and capitalize on new marketing initiatives.

Moderator: Nidhi Gupta VP Digital Channels and Senior Product Manager
Bank of America

Gildas Bah Data Engineering Analyst
Harvard Business School Online

Laura Hamilton VP Product
Rally Health

Nathan Susanj VP Head of NLP and Speech Capabilities Development
Wells Fargo

3pm

Machine Learning and the Future of Local News – STAGE 2

Local news is at a crossroads. According to a study by Poynter, trust is up. But so are layoffs and the number of communities without local news coverage. How can cash-strapped publishers continue to create journalism that will inform neighborhoods and effect change in their towns and cities? In this session, we’ll look at ways The Associated Press utilizes machine learning to produce more data-driven journalism that publishers can use to tell the stories of their communities. Specific examples will include journalism that drove policy and legislative change, as well as tips and lessons learned on how to blend the power of data with the judgment of humans.

Ken Romano Director of Product
Associated Press

3:45pm

MLOps: Challenges and Progress in Deploying Machine Learning in Production – STAGE 2

Deploying machine learning in production comes with a lot of challenges. For example, doing proper CI/CD for ML is quite hard. At Google Cloud, we’re actively working on providing a technical framework for MLOps which includes all aspects of operationalizing ML in production. In this talk, I will discuss the general concepts of MLOps and CI/CD as they apply to ML in production. I will do a deeper dive into some technical options for CI/CD with ML on GCP, using Kubeflow Pipelines as the reference platform.

Lukman Ramsey Cloud Solutions Architect
Google

3:50pm

Networking Break & Start Up Demos

Starting at 4pm

4:30pm

Strategies for Building Machine Learning Technologies that Scale and Adapt – STAGE 2

Building systems that can scale and adapt to the ever-changing compute, storage and networking landscape is a major challenge in machine learning. Michael will define strategies for creating long-lasting machine learning technologies, including optimizing computing power and costs, using capabilities on the edge and in the cloud, and taking dynamic approaches to sensing, evaluation and data routing. He will show how these strategies are implemented in Lytx’s Distributed Machine Learning Platform, which continuously monitors 600,000 fleet vehicles deployed across the world.

Michael Phillippi VP, Technology
Lytx

4:30pm

TBD Session – STAGE 2

Starting at 5pm

5pm

Transforming Enterprise Risk Management Using AI – STAGE 1

Using several real-world examples, we illustrate how we used AI to transform the ERM function from an audit-centric role to a value-add function that proactively identifies and mitigates enterprise-wide risks.

Aziz Lookman Chief Analytics Officer
Rational AI

Mihaela Nistor Head of Enterprise Risk Management
Bloomberg

Alex Sanchez Global Head of Risk Strategy and Data Analytics
Bloomberg

5pm

Transfer Learning for Model as a Service – STAGE 2

ransfer Learning for Model as a Service Training Machine learning models is a rather expensive task which requires resources – e.g. training data, gpu’s and the technical expertise – to ensure the performance of the model matches the product requirements or industry standards. Once the training is complete the investment may then be suitable only for a unique use case. We present transfer learning, as well as the steps to optimize it, as a potential solution for reducing investment in training and improved fungibility.

Anand Dwivedi Senior Data Scientist
Nasdaq

Ruchir Vani Software Engineer–Machine Intelligence Lab
Nasdaq

5:30pm

Kick-Off Party and Speaker Meet & Greet

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Location

Convene, 225 Liberty Street, New York, NY 10080

Venue & Hotel Block Info

CONVENE 225 LIBERTY STREET

CONFERENCE VENUE

Convene at 225 Liberty Street is the newest place to host large-scale events in Downtown NYC. The premium, full-service venue includes nearly 75,000 square feet of meeting and event space and can host up to 1000 people, making it perfect for conferences, trade shows, exhibits and large summits. Located within Brookfield Place, a flagship luxury shopping, dining and cultural experience center, Convene will become the ultimate destination to host meetings and events in NYC. With design inspiration stemming from the local history of Battery City, the modern framework will be a base layer of wooden ship construction materials and overlapping textures inspired by nature so visitors will experience a sense of comfort and warmth while working in the space.

HOTEL BLOCK

We have negotiated a special room rate for the event for $339 per night at the Gild Hall, located at 15 Gold Street, New York, NY. Book your discounted room at the using the following link: here.

The room rate expires on October 4th and valid only for the dates November 5th-8th, please book as soon as possible in order to secure your discounted rate.

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