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.

Likeminded Attendees

Tired of suits sitting next to you at a "data" conference? We are too, so that's why our attendees are highly-skilled data scientists, engineers, analysts and engineering managers from top companies and startups.

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 Speakers In New York City

Reza Shiftehfar

Reza Shiftehfar

Software Engineering Manager, Hadoop Platform

Reza Shiftehfar

Reza Shiftehfar

Software Engineering Manager, Hadoop Platform

Reza currently leads the Hadoop-Platform team at Uber where his team builds the required reliable/scalable data platform that serves petabytes of data utilizing technologies such as Hadoop, Hive, Kafka, Spark, Presto, etc. Reza is one of the founding engineers of the data at Uber and helped scale Uber's data platform from a few TB to 100+ PetaBytes while reducing the big data latency from 24+ hours down to minutes. Reza holds a Ph.D. degree in Computer Science from the University of Illinois @ Urbana-Champaign and had previously worked at Twitter and Apple on similar infrastructure/big data platforms.

If you are interested in the area of distributed systems and Big Data analytics and want to follow up with Reza, you can reach him on LinkedIn (https://linkedin.com/in/reza-shiftehfar-39301b6/) or on Twitter (https://twitter.com/RezaSH).

Willy Lulciuc

Willy Lulciuc

Data Engineer

Willy Lulciuc

Willy Lulciuc

Data Engineer

Willy Lulciuc is a Data Engineer at WeWork and works on the Project Marquez team in San Francisco, making datasets discoverable and meaningful. Previously, he worked on the real-time streaming data platform powering BounceX, and before that, designed and scaled sensor data streams at Canary. When he's not reviewing code and creating indirections, he can be found experimenting with analog synthesizers.

Kamil Bajda-Pawlikowski

Kamil Bajda-Pawlikowski

CTO

Kamil Bajda-Pawlikowski

Kamil Bajda-Pawlikowski

CTO

Kamil is a technology leader in the large scale data warehousing and analytics space. He is CTO of Starburst, the enterprise Presto company. Prior to co-founding Starburst, Kamil was the Chief Architect at the Teradata Center for Hadoop in Boston, focusing on the open source SQL engine Presto. Previously, he was the co-founder and chief software architect of Hadapt, the first SQL-on-Hadoop company, acquired by Teradata in 2014.

Jean-Mathieu Saponaro

Jean-Mathieu Saponaro

Data Engineer & Internal Analytics Team Lead

Jean-Mathieu Saponaro

Jean-Mathieu Saponaro

Data Engineer & Internal Analytics Team Lead

Jean-Mathieu is a Data Engineer at Datadog. As the first member of the Internal Analytics team, he designed and built data pipelines from scratch using Luigi, Spark, and Parquet files stored in S3. As the team grew, he worked on making the pipelines highly fault tolerant, reusable, and observable. He also deployed a scalable self-serve analytics platform throughout the organization for easy, accurate, and appropriate access to all internal data.

Maryam Jahanshahi

Maryam Jahanshahi

Research Scientist

Maryam Jahanshahi

Maryam Jahanshahi

Research Scientist

Maryam runs research at TapRecruit, a startup that is building software tools to implement evidence-based talent management. TapRecruit's research program integrate recent advances in NLP, data science and decision science to identify robust methods to reduce bias in talent decision-making and attract more qualified and diverse candidate pools. In a past life, Maryam was a cancer biologist and a data journalist. She holds a PhD from the Icahn School of Medicine at Mount Sinai.

Mark Weiss

Mark Weiss

Senior Software Engineer

Mark Weiss

Mark Weiss

Senior Software Engineer

Mark Weiss is a Senior Software Engineer at Beeswax, the online advertising industry’s first extensible programmatic buying platform, where he focuses on designing and building data processing infrastructure and applications supporting reporting and machine learning. He has previously held various engineering individual contributor and leadership roles, and has worked on ETL systems and data-driven distributed platforms for much of his career. Mark has spoken previously at DataEngConf NYC, and regularly speaks and mentors at the NYC Python Meetup. He is also blogs and hosts the podcast "Using Reflection" at http://www.usingreflection.com, and can be found on Github, Twitter and LinkedIn under @marksweiss. He lives in Brooklyn, NY

Andreas Mueller

Andreas Mueller

Associate Research Scientist

Andreas Mueller

Andreas Mueller

Associate Research Scientist

Andreas Mueller is a lecturer at the Data Science Institute at Columbia University and author of the O'Reilly book "Introduction to machine learning with Python", describing a practical approach to machine learning with python and scikit-learn. He is one of the core developers of the scikit-learn machine learning library, and has been co-maintaining it for several years. He is also a Software Carpentry instructor. In the past, he worked at the NYU Center for Data Science on open source and open science, and as Machine Learning Scientist at Amazon.

Jennifer Prendki

Jennifer Prendki

VP of Machine Learning, Figure Eight

Jennifer Prendki

Jennifer Prendki

VP of Machine Learning, Figure Eight

Jennifer Prendki is currently the VP of Machine Learning at Figure Eight, the essential human-in-the-loop AI platform for data science and machine learning teams. She has spent most of her career creating a data-driven culture wherever she went, succeeding in sometimes highly skeptical environments. She is particularly skilled at building and scaling high-performance Machine Learning teams, and is known for enjoying a good challenge.

Trained as a particle physicist (she holds a PhD in Particle Physics from Sorbonne University), she likes to use her analytical mind not only when building complex models, but also as part of her leadership philosophy. She is pragmatic yet detail-oriented. Jennifer also takes great pleasure in addressing both technical and non-technical audiences at conferences and seminars, and is passionate about attracting more women to careers in STEM.

Ethan Rosenthal

Ethan Rosenthal

Machine Learning Engineer

Ethan Rosenthal

Ethan Rosenthal

Machine Learning Engineer

Ethan is a Machine Learning Engineer at Dia&Co, a plus-sized women's retailer. He lead a team of scientists, engineers, and analysts focused on Styling and Customer Growth algorithms. He got his start in data science working at Birchbox. Prior to that, he earned a PhD in Physics from Columbia University where he studied unconvential superconductors.

Till Bergmann

Till Bergmann

Data Scientist

Till Bergmann

Till Bergmann

Data Scientist

Till Bergmann is a Senior Data Scientist at Salesforce Einstein, building platforms to make it easier to integrate machine learning into Salesforce products, with a focus on automating many of the laborious steps in the machine learning pipeline. Before Salesforce, he obtained a PhD in Cognitive Science at the University of California, Merced, where he studied collaboration patterns of academics using NLP techniques.

Allison King

Allison King

Software Engineer

Allison King

Allison King

Software Engineer

Allison is a software engineer at Cortico, a nonprofit that helps elevate local voices and share stories from communities all over the United States. Previously, she worked at MIT Lincoln Laboratory, researching secret stuff for the Department of Defense.

Tony Jebara

Tony Jebara

Director of Machine Learning

Tony Jebara

Tony Jebara

Director of Machine Learning

Tony is Director of Machine Learning at Netflix and is sabbatical professor at Columbia University. He served as general chair of the 2017 International Conference on Machine Learning. He has published over 100 scientific articles in the field of machine learning and has received several best paper awards. He has co-founded and advised multiple AI startups.

Jeff Smith

Jeff Smith

Engineering Manager

Jeff Smith

Jeff Smith

Engineering Manager

Jeff Smith builds AI technology and the teams behind them. Currently, he supports the team building the open source PyTorch AI platform at Facebook AI Research and beyond. He’s the author of Machine Learning Systems: Designs that scale. While working at the intersection of functional programming, distributed systems, and machine learning, he coined the term reactive machine learning to describe an ideal machine learning architecture and associated set of techniques. Prior to joining FAIR, he built teams and technology for AI products like x.ai and Amelia.

Baron Schwartz

Baron Schwartz

Founder & CTO

Baron Schwartz

Baron Schwartz

Founder & CTO

Baron is the CTO and founder of VividCortex, the best way to see what your production database servers are doing. Baron has written a lot of open source software, and several books including High Performance MySQL. He’s focused his career on learning and teaching about scalability, performance, and observability of systems generally (including the view that teams are systems and culture influences their performance), and databases specifically.

Carolyn Huangci

Carolyn Huangci

Associate Data Scientist

Carolyn Huangci

Carolyn Huangci

Associate Data Scientist

Carolyn Huangci is a data scientist at BuzzFeed, a media and tech company. She works on the Network Growth team focused on growing content views across BuzzFeed destinations. Prior to BuzzFeed she worked at Uber. She received her Bachelors in Applied Mathematics from University of California Berkeley.

Saurabh Bajaj

Saurabh Bajaj

Software Engineer

Saurabh Bajaj

Saurabh Bajaj

Software Engineer

Saurabh Bajaj is a software engineer and tech lead on Lyft's Machine learning Platform. ML Platform builds out systems for acclerating ML development, training and serving of models. Prior to Lyft, Saurabh worked at Instagram and Facebook.

Neelesh Salian

Neelesh Salian

Software Engineer - Data Platform

Neelesh Salian

Neelesh Salian

Software Engineer - Data Platform

Neelesh Srinivas Salian is a Software Engineer in the Data Platform team at Stitch Fix, where he works on building the Compute Infrastructure used by Data Scientists. Previously, he worked at Cloudera, where he worked on Apache projects like YARN, Spark, and Kafka.

Wes Chow

Wes Chow

Director of Engineering, Advanced Analytics

Wes Chow

Wes Chow

Director of Engineering, Advanced Analytics

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.

Ryan Williams

Ryan Williams

Software Engineer

Ryan Williams

Ryan Williams

Software Engineer

Ryan is a software developer at Mount Sinai School of Medicine, focused on open-source tools for distributed genomic- and single-cell analyses in the cloud.

Harlan Harris

Harlan Harris

Director of Data Science

Harlan Harris

Harlan Harris

Director of Data Science

Harlan Harris has a PhD in Computer Science/Machine Learning from the University of Illinois at Urbana-Champaign, and worked as a Cognitive Psychology researcher before turning to industry. He has worked at Kaplan Test Prep, the Advisory Board Company, and startups including WayUp and Teachers Pay Teachers. Harlan also co-founded the Data Science DC Meetup and Data Community DC, Inc., and co-wrote Analyzing the Analyzers, a short O'Reilly book about the variety of data scientists. Follow him on Twitter and Medium at @harlanh.

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

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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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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 Sailan

Senior Software Engineer
Stitch Fix

Neelesh Sailan
Data Council is a really a great conference for technical talks with real insights to data engineering challenges and solutions. As an engineer who works on open-source software I found it helpful to hear first hand from users that are working on real world challenges.

Maximilian Michels

PMC Member Apache Flink & Apache Beam
Independent Contractor @ Google

Maximilian Michels

Pre-register for Data Council New York City '19
Hapenning Dec 2-3rd, 2019

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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.

  • - 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.

  • - Inspiring keynotes and practical, information-rich sessions, tutorials, and speakers office hours exploring the latest advances, case studies, and best practices.

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

Topics Covered at Data Council

AI Features & Products
Analytics
Data Science
Data Engineering
Data Infrastructure

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