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.

Multiple Unique Tracks

This year we are going all in and offering you new unique tracks, but it's a little to early to announce all the details surronding these tracks. Please check back as we get closer to the event date.

Max - 500

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

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 for the community, for free.

Community Powered

We are a diverse group of geeks, coders, scientists, analysts (& a former astronaut serving your lunch). We care deeply about local data communities, no big $/€ sponsors here, just data nerds, like you & I.

Networking that works

Experience our popular "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.

Previous Track Hosts

Jennifer Prendki

Founder & CEO

Alectio

Neelesh Srinivas Salian

Software Engineer

Stitch Fix

Previous Speakers In New York City

 

Willy Lulciuc

Data Engineer

WeWork

Jean-Mathieu Saponaro

Data Engineer & Internal Analytics Team Lead

Datadog

Maryam Jahanshahi

Research Scientist

TapRecruit

Mark Weiss

Senior Software Engineer

Beeswax

Andreas Mueller

Associate Research Scientist

Data Science Institute, Columbia University

Jennifer Prendki

Founder & CEO

Alectio

Ethan Rosenthal

Machine Learning Engineer

Dia&Co

Till Bergmann

Data Scientist

Salesforce

Allison King

Software Engineer

Cortico

Tony Jebara

Director of Machine Learning

Netflix

Jeff Smith

Engineering Manager

Facebook AI Research

Baron Schwartz

Founder & CTO

VividCortex

Carolyn Huangci

Associate Data Scientist

BuzzFeed

Saurabh Bajaj

Software Engineer

Lyft

Wes Chow

Director of Engineering, Advanced Analytics

Cortico

Ryan Williams

Software Engineer

Icahn School of Medicine at Mount Sinai

Julian Hyde

Architect

Looker

Jacques Nadeau

Co-founder & CTO

Dremio

Sahaana Suri

Graduate Researcher

Stanford University, Future Data Systems

Mike Freedman

Co-founder & CTO

TimescaleDB

Sam Stokes

Engineer

Honeycomb

Jason Ganetsky

Senior Software Engineer and Tech Lead

Google

Marianne Bellotti

Data Engineer

United States Digital Service

Ozgun Erdogan

CTO

Citus Data

Sanjay Krishnan

Graduate Researcher

UC Berkeley, AMPLab

Burak Yavuz

Software Engineer

Databricks

Gandalf Hernandez

Data/Backend Engineering Manager

Spotify

Darren McCleary

Software Engineer

The New York Times

Christian Romming

Founder & CEO

ETLeap

Vadim Semenov

Data Engineer

Datadog

Tarush Aggarwal

Director of Data Engineering

WeWork

Genevieve Smith

Director of Product

Insight

James Faghmous

Asst. Prof/ CTO of Arnhold Institute

Icahn School of Medicine at Mt. Sinai

Lucy Wang

Senior Data Scientist

BuzzFeed

Anne Bauer

Senior Data Scientist

The New York Times

Peter Lenz

Senior Geospatial Analyst

Dstilery

Jeffrey Doker

Data Scientist

Kickstarter

Jim Klucar

Director of Data Science

Immuta

Haile Owusu

Chief Data Scientist

Mashable

Jonathan Roberts

Chief Innovation Officer

Dotdash

Chris Wiggins

Chief Data Scientist

New York Times

Claudia Perlich

Chief Data Scientist

Dstillery

Shawndra Hill

Senior Researcher

Microsoft

George Davis

Founder & CEO

Frame.ai

Neelesh Srinivas Salian

Software Engineer

Stitch Fix

Frank McSherry

Independent Researcher & Scientist

Luis Capelo

Head of Data Products

Forbes

Harlan Harris

Director of Data Science

WayUp

William Nelson

Principal Data Scientist

Intent Media Inc

Benn Stancil

Chief Analytics Officer

Mode

Raghu Murthy

Founder & CEO

Datacoral

Andreas Markmann

Data Engineering Manager

Capital One

Thomas La Piana

Data Engineer

GitLab

Sam Swift

Head of Data & AI

Bowery Farming

Dan Goldin

VP Engineering

TripleLift

Brian Bloniarz

Director of Data Science

Second Measure

William Falcon

Co-founder

NextGenVest

Hossein Azari

Co-founder

Clarity Money

Joy Tang

CEO & Founder

Markable AI

Gideon Mendels

Co-founder & CEO

Comet.ml

Nicolas Joseph

VP of Engineering & CISO

Datalogue

Phil Roth

Data Scientist

Endgame

Rigel Swavely

Senior Machine Learning Engineer

Clarifai

Alp Kucukelbir

Chief Scientist

Fero Labs

Justin Coffey

Engineering Director

Criteo Labs

Aditya Jami

CTO

Meltwater

Stephanie Yang

Data Scientist & Technical Lead

Foursquare

Marlene Guraieb

Senior Data Scientist

Oscar

Sameer Yami

Head of Architecture & AI

Linc Global

Brian Femiano

Senior Data Engineer

Pandora

Sean Glover

Senior Software Engineer, Fast Data Team

Lightbend, Inc

Adam Kelleher

Chief Data Scientist for Research

Barclays Investment Bank

James Savage

Head of Data Science

Lendable

Greg Neiheisel

Co-Founder & CTO

Astronomer

Jonathan Medwig

Jonathan Medwig

Data Engineer

Skywatch

Colin Nichols

Colin Nichols

Director Of Engineering

Narrativ

John Davies

Head of Data Science

Simon Data

Eric Novik

Founder & CEO

Generable

Eliot Knudsen

Data Science Lead

Tamr

Andy Turley

Lead Software Engineer

Wallaroo Labs

John Urbanik

Lead Data Engineer

Predata

Sonia Sen

Head of Product

Datalogue

Brunno Attorre

Co-Founder & CTO

URU

Evan Jones

Software Engineer

Bluecore

Greg Ratner

Co-Founder & CTO

Troops

Ben Davis

Co-Founder & CTO

Gather

Liz Maida

Founder & CEO/CTO

Uplevel Security

Bring your team and save!

We want to invite not just you, but your team and colleagues as well. So if you purchase 3 tickets together you will receive 1 complimentary conference pass.Look out for the “Buy 3 - Get 1 Free” pass at checkout.
(Just pay the fourth ticketing fee)


New-York-Group-Promo

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.

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.

Conference Tracks

Databases

Read more

This track focuses on databases particularly tailored to data science tasks, and to the application of machine learning to the construction of databases. Talks should be about the design of large scale databases particularly with respect to usage and implementation in a data science context. Are there certain schemas that are good for certain tasks? Are there specialized databases aimed at solving certain classes of problems? Active database research also poses a variety of optimization problems, for which we've discovering effective machine learning algorithms. How does this affect the next generation of databases? How does machine learning open up new kinds of queries and insights we can extract from our systems? This track is for those interested in state of the art data systems and the new kinds of applications they're enabling.

Machine Learning Workflows and Platforms

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This track will talk about the practice of moving machine learning systems from development to deployment, and the next generation tooling that makes this an organic process. Removing barriers to deployment allow data scientists to gain quicker feedback and deeper insights into how models are performing in the wild, and enable nimbler experimentation at the product level. To do this, new machine learning workflows are taking advantage of serverless and container orchestration technologies, and also specializing frameworks towards certain classes of data science problems. This track is for the hands on practitioners who fluidly cross the boundary between research and deployment.

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. Examples of talks include case studies on how applications use messaging systems, how applications maintain consistency and correctness while ingesting large amounts of data, and computational frameworks for processing data with low latency. This is a practical track for anybody 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. Talks will be slightly more speculative, and represent the state of the art of data science and machine learning. Good examples include academic talks aimed at solving hard problems in data science, technology-focused talks from startups aiming to commercialize new technologies, and product talks (possibly post-mortem!) about attempts to use new technologies to deliver business value. 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 who in interested in listening to an occasional academic-level research talk.

Core Data Science

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This track focuses on applications of ML and analytics methods in a product context. It can include new approaches to ML, as long as projects show solid proofs of value. Examples include AB testing analysis methods, interesting product case studies, applications of ML algorithms to generate business value, reviews of the state of the art (e.g. best practices talks for production model validation), and similar context-focused technical talks. The goal of this track is to share best practices about everyday data science practice, to learn from each other's hard lessons, and to keep everyone up to date with technologies that have proven their value. This track is for the everyday data scientist, or engineers wanting to learn more about what data science is all about. Talks will often get into some technical detail, but should 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. Throughout our conference series, we've found that bringing together an assortment of different types and sizes of companies, as well as a mix of professional roles who openly discuss organizational and cultural challenges is the best way to further the development of mature data organizations across industries. This track aims to share and spread that knowledge. Furthermore, 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. This track will be applicable to you if you are an engineering or data manager, if you are interested in building a stronger organizational culture around data teams, or if you are concerned about policy and ethical considerations surrounding the use of data in your organization.

Our Place In New York City

columbia university data councilOur big apple Data Council event is hosted annually at Columbia University in the City of New York. This ivy-league education facility is world-renowned for it's accomplished alumni, rich history and commitment to education and research. It is conveniently located close to down-town New York City and a short drive away from the Jersey side.

 

 

Featured Talks in New York City

VIEW MORE TALKS

Pricing

 

  Super Early Bird
$699
Sold Out
Early Bird
$799
Sold Out
Regular Ticket
$949
On Sale
Late Bird
$1099
Not on sale
Access to the Entire Event + All Tracks
Free Breakfast, Lunch, Snacks & Drinks
Access to Breakout Sessions

Access to Speaker Office Hours

Free Event After-Party

Early Access to Conference Recordings

No Bullshit Guarantee* (See below)

 
 

VIEW THE SCHEDULE

Apr 17, 2019 1548320400000

Welcome, announcements & track host intros (Pete Soderling)

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Apr 17, 2019 1548321300000

Keynote 1

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Apr 17, 2019 1548324000000

Talk 1

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View Venue Location

FEATURE SLIDER

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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
VividCortex

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:

crux-transparent
DataDog
Qubole
Capital One
IBM
Ascend
Partner With Us

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.

How Do We Stack Up Against The Other Guys?

  Data Council     QCon.ai    O'Reilly Strata Gartner® Data
Early Bird Ticket PriceLowest published price without any discounts, coupon codes etc. $699 $1,620 $1,645 $3,700
2 Full Days of EventsMinimum length of the conference or event.        
Food & Drinks IncludedIs some form of food, drinks or snacks provided.        
Multiple Unique TracksAre multiple unique tracks with separate content offered. These tracks can be shorter than the full length of the conference or event.         
Community PoweredDoes this conference represents a global community of attendees engaged in monthly branded meetups around the world. AND Is the vetting process democratized, or otherwise open to the public.        
Speaker Office HoursDoes the conference or event offer Speakers Office Hours.        
Open Call for SpeakersAre the speaker submission, review & acceptance process open to or including the public.        
Max 500 AttendeesIs the conference limited to under 500 attendees, in order to maximize the value for attendees.        
Free Community PartyIs there an event after-party offered (dinners not included)        
Offers a Refund PolicyYou can get your ticket refunded up to 45 days before the conference        
Has a dedicated "Sponsors Track"Does the event or conference force all sponsors into one unique track where all sponsors give talks (labeled or not). Nope      
Upsells you on extrasOffers extra workshops, tracks, recordings, sessions or other additions which are charged separately from the conference or event ticket price. Absolutely not      
Full of non-technical peopleDoes the conference or event publically invite non-technical data engineers or scientists. Definitely not      
  Data Council
Early Bird Ticket PriceLowest published price without any discounts, coupon codes etc. $699
2 Full Days of EventsMinimum length of the conference or event.  
Food & Drinks IncludedIs some form of food, drinks or snacks provided.  
Multiple Unique TracksAre multiple unique tracks with separate content offered. These tracks can be shorter than the full length of the conference or event.  
Community PoweredDoes this conference represents a global community of attendees engaged in monthly branded meetups around the world. AND Is the vetting process democratized, or otherwise open to the public.  
Speaker Office HoursDoes the conference or event offer Speakers Office Hours or similar product.  
Open Call for SpeakersAre the speaker submission process open to the public.  
Max 500 AttendeesIs the conference limited to under 500 attendees, in order to maximize the value for attendees.  
Free Community PartyIs there an event after-party offered (dinners not included)  
Offers a Refund PolicyYou get your ticket refunded up to 45 days before the conference  
Has a dedicated "Sponsors Track"Does the event or conference force all sponsors into one unique track where all sponsors give talks (labeled or not). Nope
Upsells you on extrasOffers extra workshops, tracks, recordings, sessions or other additions which are charged separately from the conference or event ticket price. Hell no!
Swarming with sales peopleDoes the conference or event publically invite non-technical data engineers or scientists. Definitely not!
  Qcon.ai
Early Bird Ticket PriceLowest published price without any discounts, coupon codes etc. $1,620
2 Full Days of EventsMinimum length of the conference or event.  
Food & Drinks IncludedIs some form of food, drinks or snacks provided.  
Multiple Unique TracksAre multiple unique tracks with separate content offered. These tracks can be shorter than the full length of the conference or event.  
Community PoweredDoes this conference represents a global community of attendees engaged in monthly branded meetups around the world. AND Is the vetting process democratized, or otherwise open to the public.  
Speaker Office HoursDoes the conference or event offer Speakers Office Hours or similar product.  
Open Call for SpeakersAre the speaker submission process open to the public.  
Max 500 AttendeesIs the conference limited to under 500 attendees, in order to maximize the value for attendees.  
Free Community PartyIs there an event after-party offered (dinners not included)  
Offers a Refund PolicyYou get your ticket refunded up to 45 days before the conference  
Has a dedicated "Sponsors Track"Does the event or conference force all sponsors into one unique track where all sponsors give talks (labeled or not).  
Upsells you on extrasOffers extra workshops, tracks, recordings, sessions or other additions which are charged separately from the conference or event ticket price.  
Swarming with sales peopleDoes the conference or event publically invite non-technical data engineers or scientists.  
  O'Reilly Strata
Early Bird Ticket PriceLowest published price without any discounts, coupon codes etc. $1,645
2 Full Days of EventsMinimum length of the conference or event.  
Food & Drinks IncludedIs some form of food, drinks or snacks provided.  
Multiple Unique TracksAre multiple unique tracks with separate content offered. These tracks can be shorter than the full length of the conference or event.  
Community PoweredDoes this conference represents a global community of attendees engaged in monthly branded meetups around the world. AND Is the vetting process democratized, or otherwise open to the public.  
Speaker Office HoursDoes the conference or event offer Speakers Office Hours or similar product.  
Open Call for SpeakersAre the speaker submission process open to the public.  
Max 500 AttendeesIs the conference limited to under 500 attendees, in order to maximize the value for attendees.  
Free Community PartyIs there an event after-party offered (dinners not included)  
Offers a Refund PolicyYou get your ticket refunded up to 45 days before the conference  
Has a dedicated "Sponsors Track"Does the event or conference force all sponsors into one unique track where all sponsors give talks (labeled or not).  
Upsells you on extrasOffers extra workshops, tracks, recordings, sessions or other additions which are charged separately from the conference or event ticket price.  
Swarming with sales peopleDoes the conference or event publically invite non-technical data engineers or scientists.  
  Gartner® Data
Early Bird Ticket PriceLowest published price without any discounts, coupon codes etc. $3,700
2 Full Days of EventsMinimum length of the conference or event.  
Food & Drinks IncludedIs some form of food, drinks or snacks provided.  
Multiple Unique TracksAre multiple unique tracks with separate content offered. These tracks can be shorter than the full length of the conference or event.  
Community PoweredDoes this conference represents a global community of attendees engaged in monthly branded meetups around the world. AND Is the vetting process democratized, or otherwise open to the public.  
Speaker Office HoursDoes the conference or event offer Speakers Office Hours or similar product.  
Open Call for SpeakersAre the speaker submission process open to the public.  
Max 500 AttendeesIs the conference limited to under 500 attendees, in order to maximize the value for attendees.  
Free Community PartyIs there an event after-party offered (dinners not included)  
Offers a Refund PolicyYou can get your ticket refunded up to 45 days before the conference  
Has a dedicated "Sponsors Track"Does the event or conference force all sponsors into one unique track where all sponsors give talks (labeled or not).  
Upsells you on extrasOffers extra workshops, tracks, recordings, sessions or other additions which are charged separately from the conference or event ticket price.  
Swarming with sales peopleDoes the conference or event publically invite non-technical data engineers or scientists.  

Competitive data collected is accurate from "qcon.ai", "conferences.oreilly.com/strata", "gartner.com/en/conferences/na/data-analytics-us", and "odsc.com/california" as of January 23, 2019. Data Council is not affiliated with any of the competitors listed. Notice an error in our data?

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BE A SPEAKER AT A DATA COUNCIL EVENT!

Want to present a talk at our next data science & engineering event? Barcelona, New York, San Francisco or Singapore, the choice is yours! Our event will include hundreds of attendees and many speakers from top data teams across different industries. To make each event better than the last, we're welcoming the community to contribute their talk ideas.

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Data Council, PO Box 2087, Wilson, WY 83014, USA - Phone: +1 (415) 800-4938 - Email: community (at) datacouncil.ai