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Keynote: Panel: Building a Data Science Capability (Live Recording of The InfoQ Podcast)

Location: Cyril Magnin Ballroom

Duration: 5:40pm - 6:30pm

Day of week: Tuesday

Abstract

What does it take to build a data science capability? What are the new roles that are being defined in a data-driven company? What do you look for in hiring a data science leader? In this panel discussion, Charles Humble (the Chief Editor of InfoQ) and Wes Reisz (Host of The InfoQ Podcast) record a live session with the organizing committee for QCon.ai to discuss these questions. Curious how to understand what they're looking for in new hires and the leaders they promote? Come learn with us in this bookend to day 1 of QCon.ai.

Host: Wes Reisz

Software/Technical Advisor C4Media & QCon Chair, previous Architect @HPE

Wes Reisz joined QCon in 2015 and leads QCon Editorial as the conference chair. Wes focuses his energies on providing a platform for practicing engineers to tell their war stories so innovative/early adopter stage engineers can learn, adopt, and, in many cases, challenge each other. Before joining the QCon Team, Wes held a variety of enterprise architecture and software development roles with HP. His focus with HP was around developing/federating identity, integration/development of Java stack applications, architecting portal/CM solutions, and delivering on mobility in places like US Army’s Human Resources Command (HRC), Army Recruiting Command, and Army Cadet Support Program. In 2002, Wes began teaching as an adjunct faculty member at the University of Louisville. He continues to teach 400-level web architecture and mobile development courses to undergraduates. He is currently teaching Mobile Application Development with Android.

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Speaker: Charles Humble

Editor-in-chief, InfoQ.com

Charles Humble took over as Editor-in-chief at InfoQ.com in March 2014, guiding the content creation including news, articles, books, video presentations and interviews. Prior to taking on the full-time role at InfoQ, Charles led our Java coverage, and was CTO for PRPi Consulting, a renumeration research firm that was acquired by PwC in July 2012. For PRPi he had overall responsibility for the development of all the custom software used within the company. He has worked in enterprise software for around 20 years as a developer, architect and development manager. In his spare time he writes music as 1/3 of London-based ambient techno group Twofish, whose debut album came out in February 2014 after 14 years of messing about with expensive toys, and spends as much time as he can with his wife and young family.

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Host: Sid Anand

Chief Data Engineer @PayPal

Sid Anand currently serves as PayPal's Chief Data Engineer, focusing on ways to realize the value of data. Prior to joining PayPal, he held several positions including Agari's Data Architect, a Technical Lead in Search @ LinkedIn, Netflix’s Cloud Data Architect, Etsy’s VP of Engineering, and several technical roles at eBay. Sid earned his BS and MS degrees in CS from Cornell University, where he focused on Distributed Systems. In his spare time, he is a maintainer/committer on Apache Airflow, a co-chair for QCon, and a frequent speaker at conferences. When not working, Sid spends time with his wife, Shalini, and their 2 kids.

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Speaker: Stephanie Yee

Data Scientist @StitchFix

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Speaker: Matei Zaharia

Assistant Professor of Computer Science @Stanford and Chief Technologist @Databricks

Matei Zaharia is an assistant professor of computer science at Stanford and Chief Technologist of Databricks, the data and ML infrastructure company based around Apache Spark. He started the Spark project while he was a PhD student at UC Berkeley. He has also contributed to other open source big data systems including Apache Mesos and Apache Hadoop. At Stanford, Matei does research on systems for machine learning as part of the DAWN project.

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Host: Soups Ranjan

Director of Data Science @Coinbase

Soups Ranjan is the Director of Data Science at Coinbase, one the largest bitcoin exchanges in the world. He manages the Risk & Data Science team that is chartered with preventing avoidable losses to the company due to payment fraud or account takeovers. Soups has a PhD in ECE on network security from Rice University. He has previously led the development of Machine Learning pipelines to improve performance advertising at Yelp and Flurry. He is the founder of RiskSalon.org, a round-table forum for risk professionals in San Francisco to share ideas on stopping bad actors.

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Tracks

  • Groking Timeseries & Sequential Data

    Techniques, practices, and approaches, including image recognition, NLP, predictions, & modeling.

  • Deep Learning in Practice

    Deep learning lessons using Tensorflow, Keras, PyTorch, Caffe including use cases on machine translation, computer vision, & image recogition.

  • AI Meets the Physical World

    Where AI touches the physical world, think drones, ROS, NVidia, TPU and more.

  • Papers to Production: CS in the Real World

    Groundbreaking papers make real world impact.

  • Solving Software Engineering Problems with Machine Learning

    Anomaly detection, ML in IDE's, bayesian optimization for config. Machine Learning techniques for more effective software engineering.

  • Predictive Architectures in the Real World

    Case Study focused look at end to end predictive pipelines from places like Salesforce, Uber, Linkedin, & Netflix.