Demystifying Data Science Conference

A FREE Live Online Conference for Aspiring Data Scientists

SEPTEMBER 27, 2017 // 10AM - 10PM EST

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Are you data curious?

Join more than 25 incredible speakers who will demystify data science, and discuss the training, the tools, and the career path to the "best job in the United States."*

*SOURCE: Glassdoor
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LIVE TALKS

Consecutive 18-minute live presentations, each followed by Q&A

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Real-time chat, with opportunities to ask questions, answer polls, and share socially.

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Meet The Speakers

Vishal Maini

Author of Machine Learning for Humans

Vishal Maini is an entrepreneur, writer, and growth marketer working to advance the positive societal impacts of artificial intelligence. He is the co-author of Machine Learning for Humans, a contributing writer at UC Berkeley's Center for Human-Compatible AI, and an advisor for edtech startup Yup Technologies. Vishal previously led growth at Upstart for four years, starting as employee #10 and eventually leading a team of nine deploying monthly marketing budgets of $1MM+. The company now has 100+ employees, has originated over $1B in loans, and is GAAP-profitable. Vishal has his Bachelor's degree in Economics from Yale University and enjoys moral philosophy, fiction, applied cognitive science, and electronic music. He wrote his first line of Python in January 2017, and has learned a few things since then.

Follow Vishal on Twitter at @v_maini.

Tim Hopper

Data Scientist at Distil Networks

Tim Hopper is a data scientist and software developer in Raleigh, North Carolina. His educational background is in mathematics and operations research. He currently works at Distil Networks where he uses machine learning to block malicious, automated web traffic.

Follow Tim on Twitter at @tdhopper.

Emily Robinson

Data Analyst at Etsy

Emily is a Data Analyst at Etsy where she works with the search team to design, implement, and analyze experiments on the ranking algorithm, UI changes, and new features. Emily earned her masters in Organizational Behavior from INSEAD in 2016 and her bachelor's in Decision Sciences from Rice University. Emily is also a graduate of the Metis Data Science bootcamp.

Follow Emily on Twitter at @robinson_es.

Kevin Markham

Founder of Data School

Kevin Markham is the founder of Data School, an online school that will help you to launch your data science career. He is passionate about teaching data science to people who are new to the field, regardless of their educational and professional backgrounds. He teaches machine learning and data analysis in Python to over 10,000 students each month through his popular YouTube channel. Prior to Data School, he co-founded a technology startup, worked for two national nonprofit organizations, served our country for two years through AmeriCorps, and worked for two seasons as a wildland firefighter. He has a degree in Computer Engineering from Vanderbilt University.

Follow Kevin on Twitter at @justmarkham.

Mara Averick

Consultant at TCB Analytics

Mara is a bit of a polymath and self-confessed data nerd. With a background in research in Science & Technology Studies, she has a breadth of experience in data analysis, visualization, and applications thereof. Currently, she's a Consultant at TCB Analytics. You can find her sharing R-related stuff on Twitter and turning technical subject matter into easy reading for non-technical audiences. When she's not talking data, she's diving into NBA stats, exploring weird and wonderful words, and/or indulging in her obsession with all things Archer.

Follow Mara on Twitter at @dataandme.

Claudia Perlich

Chief Data Scientist, Dstillery

Claudia Perlich is the Chief Data Scientist at Dstillery. Prior to joining Dstillery (formerly at Media6Degrees), she spent five years working at the Data Analytics Research group at the IBM T.J. Watson Research Center, concentrating on research in data analytics and machine learning for complex real-world domains and applications. She has been published in over 30 scientific publications and holds multiple patents in the area of machine learning. Claudia has won many data mining competitions, including the prestigious 2007 KDD CUP on movie ratings, the 2008 KDD CUP on breast-cancer detection, and the 2009 KDD CUP on churn and propensity predictions for telecommunication customers. Claudia received her Ph.D. in Information Systems from Stern School of Business, New York University in 2005, and holds a Master of Computer Science from Colorado University.

Follow Claudia on Twitter at @claudia_perlich.

Deborah Berebichez

Chief Data Scientist, Metis

Deborah Berebichez is a physicist, data scientist and TV host. She has expertise in scientific research and advanced analysis and she has helped automate decision-making and uncover patterns in large amounts of data. Her passion lies in merging critical thinking skills with practical coding skills. She specializes in drawing connections between the approaches used in data science and the challenges organizations face. Deborah has a Ph.D. in physics from Stanford and completed two postdoctoral fellowships at Columbia University's Applied Math and Physics Department and at NYU's Courant Institute for Mathematical Sciences. She is a frequent mentor of young women in STEM. Her work in science education and outreach has been recognized by the Discovery Channel, WSJ, Oprah, Dr. Oz, TED, DLD, WIRED, Ciudad de las Ideas and others.

Follow Deborah on Twitter at @debbiebere.

Chris Albon

Co-Host/Co-Founder, Partially Derivative

Chris Albon is a data scientist. He founded the TechStars company New Knowledge and is also the co-host of the data science podcast, Partially Derivative. Previously, he led Ushahidi's work on crisis and humanitarian data and launched CrisisNET. Prior to Ushahidi, he was Director of the Governance Project at FrontlineSMS. He is also known for his machine learning flashcards. He earned a Ph.D. in Political Science from the University of California, Davis researching the quantitative impact of civil wars on health care systems. He earned a B.A. from the University of Miami, where he triple-majored in political science, international studies, and religious studies.

Follow Chris on Twitter at @ChrisAlbon.

Kirk Borne

Principal Data Scientist, Booz Allen Hamilton

Dr. Kirk Borne is an Executive Adviser and the Principal Data Scientist at Booz Allen Hamilton (since 2015). He previously spent 12 years as Professor of Astrophysics and Computational Science at George Mason University where he taught and advised students in the graduate and undergraduate Data Science degree programs. Before that, he worked 18 years on NASA projects, developing and managing large data systems for space science research, including a term as the NASA Project Scientist for the Hubble Space Telescope Science Data Archive, and several years as contract Program Manager in NASA's Space Science Data Operations Office. He is an active contributor on social media, where he has been named consistently among the top worldwide influencers in big data and data science since 2013. In 2014 he was named an IBM Big Data and Analytics Hero, and in 2016 he was elected Fellow of the International Astrostatistics Association.

Follow him on Twitter at @KirkDBorne.

Megan Ayraud

Head of Careers, Metis

As Head of Careers for Metis, Megan has successfully coached and supported hundreds of people through their data science job search including: creating a personalized career strategy, identifying open job opportunities, providing introductions, preparing candidates for interviews, and navigating them through the salary negotiation process. Megan is passionate about helping people identify the right career choices and jobs they love. She got her Bachelor's degree in Political Science from Pepperdine University.

Follow Megan on Twitter at @missmegana22.

Claudia Perlich

Chief Data Scientist, Head of Dstillery

Claudia Perlich is the Chief Data Scientist at Dstillery. Prior to joining Dstillery (formerly at Media6Degrees), she spent five years working at the Data Analytics Research group at the IBM T.J. Watson Research Center, concentrating on research in data analytics and machine learning for complex real-world domains and applications. She has been published in over 30 scientific publications and holds multiple patents in the area of machine learning. Claudia has won many data mining competitions, including the prestigious 2007 KDD CUP on movie ratings, the 2008 KDD CUP on breast-cancer detection, and the 2009 KDD CUP on churn and propensity predictions for telecommunication customers. Claudia received her Ph.D. in Information Systems from Stern School of Business, New York University in 2005, and holds a Master of Computer Science from Colorado University.

Follow Claudia on Twitter at @claudia_perlich.

Carla Gentry

Data Scientist, Talent Analytics

Carla is an acknowledged influencer and subject matter expert in the field of advanced analytics and data science. During the past 19 years, Carla has worked with Fortune 100 and 500 companies including but not limited to, Discover Financial Services, J&J, Hershey, Kraft, Kellogg’s, SCJ, McNeil, PBA, Disney, Deloitte and Firestone. Carla has multiple degrees in Mathematics and Economics from the University of Tennessee where she graduated tops in her class while raising two boys as a single mom. Carla has joined forces with Talent Analytics to spread the word of predictive and workforce analytics for pre-hire employment and retention/goodness of fit. Carla commented that after watching the wrong people being hired into companies over the last 20 years and leaving companies due to bad managers and teams that didn’t work, she wanted to be a part of change in the hiring process.

Follow Carla on Twitter @data_nerd.

Bob Hayes

President, Business Over Broadway

Bob Hayes is a researcher, writer and consultant. He likes to solve problems using the scientific method, and his interests are at the intersection of customer experience, data science and analytics. Bob holds a PhD in industrial-organizational psychology and has written three books on the topic of customer experience, measurement and analytics and blogs regularly on these topics. He is considered a top social influencer in the data science and machine learning space.

Follow Bob on Twitter at @bobehayes.

Sebastian Gutiérrez

Data Scientist and Data Visualizer

In Data Science, Sebastian co-founded DataScienceWeekly.org to provide news and commentary in data science. The Data Science Weekly newsletter reaches tens of thousands of aspiring and professional data scientists on a weekly basis. Sebastian is the author of Data Scientist at Work, a collection of interviews with many of the world’s most influential data scientists. Sebastian is also the co-author of the "Get A Data Science Job Course," a three-part guide to getting started in data science, constructing your data science portfolio, and building a data science resume.In Data Visualization, Sebastian founded DashingD3js.com to provide online and corporate training in data visualization and D3.js to a diverse client base, including corporations like the New York Stock Exchange, the American Express Company, Intel, General Dynamics, Salesforce, Thomson Reuters, Oracle, Bloomberg Businessweek, universities (MIT, Georgia, and others), and dozens of startups. More than 1,000 people have attended his live trainings and many more have succeeded with his online D3.js training. Sebastian Gutierrez holds a BS in Mathematics from MIT and an MA in Economics from the University of San Francisco.

William Chen

Data Scientist, Quora

William Chen is a data scientist at Quora, where he leads data science efforts surrounding questions on Quora. He is also an avid writer and 4x Top Writer on Quora, where he answers questions about data science, statistics, machine learning, and how to make the career transition to data science. He has a passion for telling stories with data and sharing advice with aspiring data scientists on Quora. His data science content has been featured on VentureBeat, HuffPost, and Forbes. William is a co-author of “The Data Science Handbook” (a collection of 25 interviews) and “The Only Probability Cheatsheet You’ll Ever Need”. William holds degrees in Statistics and Applied Mathematics from Harvard University.

Follow William on Twitter at @wzchen.

Ryan Swanstrom

Director of Data Science, Matisia Consultants

Since creating the first data science specific blog on the internet in 2012, Ryan Swanstrom has been named as a thought-leader in big data and listed as one of the most influential people on the internet for data science. Ryan currently works as the Director of Data Science for Matisia Consultants, where he helps companies use data to solve problems. He lives in South Dakota with his wife and five children.

You can follow Ryan's Data Science 101 blog or follow Ryan on Twitter @ryanswanstrom.

Rumman Chowdhury

Senior Manager, Accenture Artificial Intelligence

Rumman's passion lies at the intersection of artificial intelligence and humanity. She comes to data science from a quantitative social science background. She holds two undergraduate degrees from MIT, a Masters in Quantitative Methods of the Social Sciences from Columbia University, and a Ph.D. from the University of California, San Diego. More recently, she has emerged as a thought leader in the San Francisco Data Science community and in mainstream media, she has been interviewed for the PhDivas podcast, German Public Television, Software Engineering Daily, RE-Work, StemGirls, and fashion line MM LaFleur. Her professional consulting experience includes the BBC, Capital One, the World Bank, and LACMA, among others. She is also the co-host of the podcast Studies Show, which is a critical take on data literacy in pop culture and mainstream media.

Follow Rumman on Twitter at @ruchowdh.

Camille Eddy

Mechanical Engineering Student and Tech Advocate

Camille Eddy is currently in her senior year studying Mechanical Engineering at Boise State University (BSU). She is also a robotics intern at X formerly known as Google X and has previously completed research in Augmented Reality at BSU, as well as robotics and machine learning research as an intern at HP Labs. Camille actively speaks around the country on topics about tech and diversity.

Follow Camille on Twitter at @NikkyMill.

Rachel Thomas

Founder & Researcher, fast.ai

Rachel Thomas has a math Ph.D. from Duke and was selected by Forbes as one of “20 Incredible Women Advancing AI Research”. She is co-founder of fast.ai and a researcher-in-residence at the University of San Francisco Data Institute. Her background includes working as a quant in energy trading, a data scientist + backend engineer at Uber, and a full-stack software instructor at Hackbright. Rachel’s writing about diversity and data science has made the front page of Hacker News 4x; been translated into Chinese, Spanish, & Portuguese; and been featured in newsletters from O’Reilly, Fortune, Mattermark, & others. She writes an ask-a-data-scientist advice column and is on twitter @math_rachel. Rachel co-founded fast.ai with the goal of making deep learning accessible to people outside of elite institutions, who are tackling problems in meaningful but low-resource areas. Over 50,000 students have started the FREE fast.ai course, Practical Deep Learning for Coders, and graduates from the course have gone on to become Google Brain residents, earned patents, gotten new job offers, won hackathons, and had their work featured in Forbes and on HBO’s Silicon Valley.

Follow Rachel on Twitter at @math_rachel.

Joel Grus

Research Engineer, Allen Institute for Artificial Intelligence

Joel Grus is a research engineer at the Allen Institute for Artificial Intelligence, the author of Data Science from Scratch, and co-host of the Adversarial Learning podcast. Previously he worked as a software engineer at Google and as data scientist at a variety of startups.

Aylee Nielsen

Analytics Community Manager, IBM

Aylee Nielsen is the Analytics Community Manager at IBM Hybrid Cloud, where she is responsible for overseeing and reimagining the 400K+ user group and nearly 150+ member IBM Analytics Champions advocacy program. She is committed to enriching vibrant user communities through tactics and practices that strive to truly empower all users and customers. In her current role, Aylee is exploring the full potential of brand advocacy and redesigning communities, large and small, that are in need of new leadership, purpose, and meaning. Previously, as Head of Influencer Engagement, she reshaped the way IBM Analytics envisioned and practiced thought-leadership while building a strong and enduring community of some of the world’s most influential data and analytics experts. She far exceeded targets, and broke records as she set new standards and restructured that influencer program. Aylee is also passionate about the art of digital storytelling, and fascinated by the exercise and psychology of perfecting shareability. Her background spans a variety of fields from Business Analytics and Visualizations to Data Science and Machine Learning to Hybrid Cloud and Data Management.

You can follow Aylee on Twitter at @AyleeNielsen.

Vin Vashishta

Founder and Chief Data Scientist, V-Squared

Vin is the founder and chief data scientist of V-Squared. He has been an applied data scientist for the last eight years and has worked in software development for 12 years before that. Yes, even on his bio there’s math. He’s been published on business strategy and machine learning topics. He speaks a bit and tweets out what he’s reading. He’s only as good as his next project so he’d better get back to it.

You can follow Vin on Twitter at @v_vashishta

Jessica Cox

Technology Researcher, Elsevier Labs

Jessica is a tech researcher at the scientific publishing company Elsevier, where she leverages her background as a biomedical scientist and machine learning to gain deeper insight into their published content. Jessica is also a graduate of the Metis Data Science bootcamp.

Andre Gatorano

Principal Data Scientist, Capital One

Andre is a Chicago native, but he has lived on both coasts. He is a data scientist, but took a few turns to get here. He was initially a bioinformatician, and found himself trying to do data science projects on biological topics. He enrolled in the Metis Data Science bootcamp to expand his tool set and apply himself not only to biological problems, but also to anything. He loves data, and we what can do and understand with it.

Naoya Kanai

Data Scientist at Airbnb

Naoya Kanai is a data scientist based in San Francisco. Before experiencing Metis both as a student and teaching assistant, he worked in diverse roles ranging from back-end development, marketing, and operations at local startups, in addition to advising multinational corporations at Bain & Company. A graduate of Stanford University and The Juilliard School, Naoya is active as a professional cellist and enjoys performing, teaching, contributing to open source, and watching soccer.

Lorena De La Parra

Data Scientist, CKM Advisors

Lorena is an International Development professional turned Data Scientist. Her previous experiences include serving as a Peace Corps volunteer in West Africa and South Africa, interning with the United Nations Development Program, acting as an Evaluation Consultant for a microfinance in Haiti, and working as a Research and Evaluation Analyst for a domestic violence organization. It was Lorena’s strong belief that the nonprofit and public sectors should have the same drive and capabilities as their for-profit counterparts that led her to Data Science. Lorena currently works as a Data Scientist at CKM Advisors and holds a dual Masters in Economics and International Political Economy and Development from Fordham University. Lorena is also a graduate of the Metis Data Science bootcamp.

Michael Lai

Data Scientist, Philadelphia 76ers

Michael found an interest in data science through his hobby of following basketball analytics. With a background in applied mathematics and economics, Michael decided to make a leap from his career as a trader -- his sights set being a data scientist with an NBA team. After a brief stint as a consultant at IBM, Michael eventually landed with the Philadelphia 76ers as a data scientist, building tools and analyzing data to help support basketball operations. Michael is also a graduate of the Metis Data Science bootcamp.

Brandon Rohrer

Data Scientist, Facebook

Brandon loves solving puzzles and building things. Practicing data science gives him the opportunity to do both in equal measure. Like most data scientists, he came to the field indirectly. He started by studying robotics and human rehabilitation at MIT, moved on to machine vision and machine learning at Sandia National Laboratories, then to predictive modeling of agriculture DuPont Pioneer, to cloud data science at Microsoft and finally to building models with global data at Facebook. In his spare time, he likes to rock climb, write robot learning algorithms, and go on walks with his wife and their dog, Reign of Terror.

You can follow Brandon on Twitter at @_brohrer_.

Renee Teate

Host, Becoming a Data Scientist Podcast

Renee Marie Parilak Teate is the host and creator of the Becoming a Data Scientist Podcast and works as a Data Scientist at HelioCampus, a higher ed analytics start-up. She has an undergraduate degree in Integrated Science and Technology from James Madison University, and a Masters in Systems Engineering from the University of Virginia. Before officially becoming a data scientist about 1 year ago, Renee worked with databases for over 10 years as a relational database designer, data-driven website developer, and SQL Data Analyst. At HelioCampus, Renee takes on a variety of roles, from SQL ETL development to Tableau dashboard design to Predictive Modeling with Python and scikit-learn to custom data analysis and training. Renee also created DataSciGuide, a data science learning resource directory, and loves chatting with people on Twitter about transitioning into data science careers.

Follow Renee on Twitter at @becomingdatasci.

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