TBD 2021

Talks That Keep You Awake!

Our talks are backed by our 100% No Bullshit Guarantee* and delivered by leading data scientists and engineers from top organizations like Facebook, Netflix, Lyft, Salesforce, Colombia University, WeWork, MIT & many more.

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5 Unique Tracks

In 2019 we offered you new unique tracks, with a total of 5 tracks covering: Databases, Machine Learning, Workflows and Platforms, Streaming Systems, Future of Data Science, Core Data Science & Data Organizations & Ethics.

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Max - 500

Tired of mega-conferences where it's hard to interact with people? We are too, so we aim to keep attendees under 500 for each of our events. Our attendees are also highly-skilled data scientists, engineers, analysts & engineering managers.

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Born To Be Open Source

We believe in Open Source; code, content and mentality. We feature top open source contributors and tools at our talks. Afterwards, we publish all content (talks and slides) for the community, for free.

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Meet People with Geekmatch

Want to meet make sure you meet awesome data people with your interests? Our new #GeekMatch service will introduce you to to a few likeminded attendees. Say goodbye to awkward introductions!

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Networking That Works

Experience our popular "Speakers Office Hours" format plus our favored Data Community Party. Through our intentional matching opportunities you'll meet data influencers who will positively impact your career.

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Previous Track Hosts

Marc Ferradou

Senior Director of Data Science


Masha Danilenko

Data Engineer

Meta (Facebook)

James Savage

Manager, Data Science

Schmidt Futures

Nitya Narasimhan

Senior Program Manager, Developer Relations


Ian Nowland

Vice President Engineering - Metrics and Alerts


Wes Chow

Director of Engineering, Advanced Analytics


Previous New York City Speakers


Zach Kulis

Director, Software Engineering, Conversational AI

Capital One

Susana Marquez

Manager, Data Scientist

Rockefeller Foundation

Lloyd Danzig

Chairman & Founder


Joshua Loftus

Assistant Professor


Abe Gong

Co-Founder & CEO

Great Expectations

Yev Meyer

Senior Data Scientist


Maureen Teyssier

Director of Data Science and Data Engineering


Mohammed Ridwanul

Product Manager


Samantha Bail

Data Insights Engineer

Shira Mitchell


Civis Analytics

Nick Rockwell

Chief Technology Officer

The New York Times

Ronny Luss

Research Staff Member

IBM Research AI

Margaret Mayer

MVP, Software Engineering for Messaging, Conversational AI and Innovation Platforms

Capital One

Sean Knapp

CEO and Founder


Barr Moses

CEO & Co-founder

Monte Carlo

Lucy Vasserman

Software Engineer


Elias Bareinboim

Associate Professor

Columbia University

Alex Kass

Engineering Manager, Observability Applications & Infra Analytics


Seth Wiesman

Solutions Architect


Tim van Cann

Data Engineer


Hugo Bowne-Anderson

Data Scientist


Liwei Mao

Team Lead


Adi Polak

Vice President of Developer Experience


Daniel van der Ende

Data Engineer


Joe Ross

Principal Data Scientist


Viktor Gamov

Developer Advocate


Adam Kelleher

Chief Data Scientist for Research

Barclays Investment Bank

Brian Femiano

Senior Data Engineer


Sean Glover

Senior Software Engineer, Fast Data Team

Lightbend, Inc

Marlene Guraieb

Senior Data Scientist


Sameer Yami

Head of Architecture & AI

Linc Global

Hossein Azari


Clarity Money

Joy Tang

CEO & Founder

Markable AI

Brian Bloniarz

Director of Data Science

Second Measure

William Falcon

AI Researcher

Facebook / NYU

Sam Swift

Head of Data & AI

Bowery Farming

Dan Goldin

VP Engineering


Andreas Markmann

Data Engineering Manager

Capital One

Thomas La Piana

Data Engineer


Aditya Jami



Stephanie Yang

Data Scientist & Technical Lead


Alp Kucukelbir

Chief Scientist

Fero Labs

Justin Coffey

Engineering Director

Criteo Labs

Phil Roth

Data Scientist


Rigel Swavely

Senior Machine Learning Engineer


Gideon Mendels

Co-founder & CEO


Nicolas Joseph

VP of Engineering & CISO


Juliana Freire

Professor of Computer Science and Engineering and Data Science


Benn Stancil

Field CTO


Raghu Murthy

Founder & CEO


Harlan Harris

Director of Data Science


William Nelson

Principal Data Scientist

Intent Media Inc

Gideon Mann

Head of Data Science


Norma Padron

Senior Director, Research

American Hospitals Association

George Talbot

Staff Software Engineer


John Maiden

Senior Data Scientist


Kai Rikhye

Senior Staff Data Engineer


Herman Schaaf

Senior Software Engineer


Riva-Melissa Tez

Sr Director, Strategic Technology Initiatives

Intel Corporation

Tony Jebara

Director of Machine Learning


Allison King

Software Engineer


Baron Schwartz

Founder & CTO


Jeff Smith

Engineering Manager

Facebook AI Research

Saurabh Bajaj

Software Engineer


Carolyn Huangci

Associate Data Scientist


Ryan Williams

Software Engineer

Icahn School of Medicine at Mount Sinai

Mark Etherington


Crux Informatics

Willy Lulciuc

Founding Engineer


Jean-Mathieu Saponaro

Data Engineer & Internal Analytics Team Lead


Mark Weiss

Senior Software Engineer


Maryam Jahanshahi

Research Scientist


Andreas Mueller

Associate Research Scientist

Data Science Institute, Columbia University

Till Bergmann

Data Scientist


Ethan Rosenthal

Machine Learning Engineer


Vadim Semenov

Data Engineer


Amelia White

Lead Data Scientist


Jerome Nilmeier

Data Scientist & Developer Advocate


Nathan VanBenschoten

Staff Software Engineer

Cockroach Labs

Frank McSherry

Chief Scientist


Committee Chair

Pete Soderling

Pete Soderling

Pete Soderling is currently the founder & CEO of Data Council. As a former software engineer, serial founder and investor in data-backed startups, his passion is in building valuable resources and community for data scientists, engineers, analysts and product managers. Previously Pete founded Hakka Labs (a social network for software engineers), Stratus Security (an early cloud-based enterprise API platform) and mechanikal (a software development consultancy in NYC). A graduate of New York University, Pete has served as a mentor for 500 Startups, has been a TEDx, O’Reilly Strata and QCon speaker and has worked with technical founders across the globe.

Previous Committee Co-Chairs

Adam Kelleher

Adam Kelleher

Adam spent more than 4 years at Buzzfeed where he was a Principal Data Scientist. Adam holds a PhD in physics. He's now heading Barclays's research data science team, and teaching applied causal inference at Columbia's Data Science Institute where he is an Adjunct Assistant Professor.

Wes Chow

Wes Chow

Wes is Director of Engineering, Advanced Analytics at Cortico. He's also Technical Advisor at Chartbeat and a Visiting Researcher at the Laboratory for Social Machines at the MIT Media Lab.

Previous Conference Tracks

Data Engineering and Beyond

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This track focuses on classic and modern data engineering workflows, databases and more. Some talks also discuss pipelines and systems that are tailored to data science and machine learning tasks.
Our speakers will cover high-level architectures, best practices and detailed solutions for designing large scale pipelines and databases, reproducibility of ML experiments, automated deployment of ML models in production, algorithms for optimization of a new generation of databases and continuous data pipeline monitoring.

This track will appeal to hands-on data engineering practitioners who fluidly cross the boundary between development and operations.

Streaming Systems

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This track looks at infrastructure used to build real-time applications and the underlying data infrastructure that supports the movement of data to computation. Speakers will cover topics such as lessons learned from moving to a Kafka-based setup, using KSQL, implementing a custom streaming SQL engine, streaming metrics and the future of event-based applications.

This is a practical track for data engineers looking to design the backbone of a data intensive application architecture.

Future of Data Science

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This track is focused on the cutting edge of data science. Stretch your brain with talks on the speculative side of the spectrum that represent the new future of data science and machine learning. This track will also cover topics such as NLP and unsupervised deep learning as well as potential applications in predicting user behavior or building knowledge graphs.

The goal of this track is to share lessons from past attempts to use new technologies, to encourage the diffusion of technology from academic research into industry, and to provide inspirational examples of the creative application of research toward creating the technologies of our future. This track is for anyone looking for inspiration to innovate in product development by applying new research, and is interested in listening to an occasional academic-level research talk.

Core Data Science

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The goal of this track is to share best practices about everyday data science from top practitioners. It features talks that cover common challenges facing data science teams and ICs – while reminding us of the tremendous power of data, analytics and ML applied in a business context. Come and learn from each other's hard lessons and avoid common pitfalls.

This track is for the everyday data scientist, or engineers wanting to learn more about what data science is all about. Talks will obviously get into technical detail, but will also be of interest to product managers wanting to understand how to do more to integrate data science into their product development process.

Data Organizations & Ethics

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This track will cover various topics related to building data organizations as well as the ethical implications of the work we do as data professionals (understanding bias, privacy implications, etc.). Some companies are just getting started with data, some have a more mature data team and process, and some simply have too much data and too small of a team to manage it! On top of it all, many are unaware (or perhaps unconcerned?) about the ethical implications of their work.

As our data teams continue to push the technical boundaries of what is possible, the ethical implications of massive data repositories combined with advanced data mining techniques, machine learning algos, and deep learning in general are raising important considerations in the area of data ethics. Ethical issues often raise discussions regarding organizational and cultural challenges as well.

This track will be applicable to you if you are an engineering or data manager who wants to build a stronger organizational culture around data, and if you are concerned about policy and ethical considerations surrounding the use of data and AI in your organization.

Max 500: We are not a “mega-conference”

We aim to keep attendees lower than 500 attendees for any Data Council event or conference. We've been there too, and we know the reason you attend conferences is not to be sold to or lose yourself in a massive sea of attendees.

Aiming for less than 500 attendees ensures that you have a fair chance to engage with speakers 1:1 on your favorite track during Speaker Office Hours. It's worth noting that this is not a watered-down "mega-conference," but an intentional community-powered conference for engineers & scientists, by engineers & scientists, like yourself!

Generally, our conferences attract between 300-500 people depending on the season, location, and speakers.

Speaker Office Hours: Meet your crowd

Most speakers hold "office hours" after their talk, which are a great opportunity to take the discussion further in a smaller setting. 

Unlike Q&A where you are usually limited to asking one question, you will be able to have an in-depth back-and-forth discussion with the speaker and like-minded attendees - a great way to learn more and build long-term relationships.

Attendees often mention Speaker Office Hours as one of their favorite perks of attending our events.

Featured Talks in New York City



Apr 17, 2019 1548320400000

Welcome, announcements & track host intros (Pete Soderling)

Apr 17, 2019 1548321300000

Keynote 1

Apr 17, 2019 1548324000000

Talk 1

View Venue Location


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What Our Attendees Say

Data Council was really great. The vibe and culture were exactly what I felt from following the RSS feeds, Twitter, watching YouTube, etc. for the last couple of years, and what attracted me to want to come to the event. I will be recommending it to friends! It was a real pleasure speaking.

Baron Schwartz

CTO & Founder

Baron Schwartz - CTO & Founder
Just wanted to reach out to thank you for the opportunity to speak at the conference. As a conference it was very informative and the talks inspired some of my software design approaches. I'm sharing my experiences with my team to help spread the knowledge.

Neelesh Salian

Senior Software Engineer
Stitch Fix

Neelesh Salian
Thanks for organizing Data Council. I really enjoyed the conference! I think you managed to build something with the right balance of tech and business content. Definitely one of the best conferences i attended this year. Not only that the talks were valuable but i enjoyed speaking to other participants. I found that many of them face similar challenges to the ones we deal with on a daily basis. Looking forward for the next one.

Gideon Mendels

Co-founder & CEO, Comet.ml

Gideon Mendels

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Data Council NYC 2019 Partners Include:

Capital One
The New York Times
Datafoam BW
Mode Analytics
Get Guru
Sponsor 2024

New York City Highlights 2019

  • - 2 days & 45+ insightful talks by leading data scientists, engineers and machine intelligence researchers from top organizations like Facebook, Salesforce, IBM, Netflix, Google, WeWork, Lyft, Stitch Fix, Datadog, Segment, Datacoral, Columbia University and many more.

  • - Multiple unique tracks featuring stuff for all data geeks. More to come later.

  • - All-new content including our brand new Founders Panel of top startup founders in the AI space.

  • - Max 500 attendees, the best attendee:speaker ratio in the business.
  • - Extensive networking opportunities at the event, or connect with speakers & attendees at after-party between event days.

  • - Small group Speaker Office Hours following each talk with an opportunity to dive deeper into the subject matter 1:1 with the speaker.

  • - Enjoy meeting attendees that are highly-technical data scientists, engineers, analysts & technical founders from top tech, media, and finance companies around the NYC area.

  • - Connect with our great partner companies at Sponsor Spotlight to discover their available data jobs, open-source projects and latest product developments.

  • - Fun evening event, giving you more face time with attendees and speakers.