Demystifying Data Science Conference

A FREE Live Online Conference for Aspiring Data Scientists & Data-Curious Business Leaders


28 Speakers • 2 Days • FREE

July 24 - July 25, 2018

10am - 5pm ET


Register by June 28th for a chance to win a free spot in our Live Online Beginner Python & Math for Data Science part-time course!

See sweepstakes official rules here.

Metis Demystifying Data Science Conference Sweepstakes Official Rules

NO PURCHASE NECESSARY TO ENTER OR WIN. A PURCHASE DOES NOT INCREASE YOUR CHANCES OF WINNING. VOID WHERE PROHIBITED. Metis Demystifying Data Science Conference Sweepstakes ("Promotion") begins on 5/21/18 at 12:00:00 AM Eastern Time ("ET") and ends at 11:59:59PM ET on 6/28/18 (the "Promotion Period").


ELIGIBILITY: The Promotion is open only to legal residents of the United States and the District of Columbia (excluding Rhode Island) who are 18 years of age or older at the time of Promotion. Employees, officers and directors of Kaplan, Inc. (the "Sponsor"), and Sponsor's parent, affiliates, subsidiaries, and advertising, contest, fulfillment and marketing agencies (all of such entities (including, but not limited to, the Sponsor) are collectively referred to herein as the, "Promotion Parties"), their immediate families (parent, child, sibling and spouse and their respective spouses, regardless of where they reside) and persons living in the same households as such individuals (whether related or not) are not eligible to participate in the Promotion. By participating, you agree to these Official Rules and to the decisions of the Sponsor, which are final and binding in all respects. Void where prohibited by law, rule or regulation. All applicable federal, state and local laws and regulations apply.

HOW TO ENTER THE SWEEPSTAKES: To enter the Promotion, you can register for the Demystifying Data Science Conference at by 11:59:59 PM ET of 6/28/18 during the Promotion Period. The Sponsor reserves the right to disqualify any entry from the Promotion for any reason.

PRIZES, DRAWINGS & ODDS OF WINNING: A total of three (3) prizes will be selected in electronic, randomized drawings. The drawing for the Prize (described below) will be held on 6/29/18 following the Promotion Period. The drawing will be from all eligible entries received during the Promotion Period. The drawing will be conducted by Sponsor using RandomPicker, whose decisions are final and binding in all matters relating to this Promotion. Odds of winning depend on the number of eligible entries received.

PRIZES: Three (3) Prizes will be awarded for the Promotion. Each Prize will consist of the following:
One enrollment in an upcoming Metis Beginner Python & Math for Data Science Live Online Professional Development Course. Winner must select one course start date from those scheduled within one calendar year from the Prize winner was notified of the award.

The Approximate Retail Value ("ARV") of each Prize is $1,250 US
* Any applicable taxes on the Prize are the sole responsibility of the winner.

WINNER NOTIFICATION: Potential winner will receive Prize notification and prize claim information via email within seventy-two (72) hours after the drawing, or as soon thereafter as reasonably practicable. Sponsor is not responsible for any change in entrant's telephone number, mailing address, and/or email. Winner will have seven (7) calendar days from time of receipt of winning notification to confirm that the notification has been received in order to claim his/her Prize. A potential winner is subject to verification, including verification of age. If such potential winner cannot be contacted within a reasonable time period, if the potential winner is ineligible, if any notification is returned undeliverable, or if the potential winner otherwise fails to fully comply with these Official Rules, he/she will forfeit that Prize and an alternate winner may be selected from all remaining entries.

GENERAL PRIZE CONDITIONS: Prize will only be awarded by Sponsor upon potential winner's verification of eligibility (if requested by Sponsor), and compliance with these Official Rules and final approval by Sponsor. No prize substitution, cash equivalent of Prize, transfer or assignment of Prize is permitted, except by Sponsor which reserves the right to substitute a Prize with one of comparable or greater value, in its sole discretion. Prize is awarded "as is" with no warranty or guarantee, either express or implied. All Prize details are at Sponsor's sole discretion. Any and all warranties and/or guarantees on a Prize (if any) are subject to the respective manufacturers' terms therefore, and winner agrees to look solely to such manufacturers for any such warranty and/or guarantee. An unclaimed Prize will not be awarded. All federal, state, local, and other taxes on a Prize and any other costs and expenses associated with Prize acceptance and use not specified herein as being provided, are the sole responsibility of the applicable winner. A 1099 tax form will be issued where required. Notwithstanding anything herein, a potential Prize winner may be required to complete and return an Affidavit of Eligibility and Liability/Publicity Release form within five (5) calendar days of attempted delivery of same. Non-compliance within this time period or return of any Prize/Prize notification as undeliverable may result in disqualification. All federal, state, municipal, provincial and local laws and regulations apply.

PUBLICITY RELEASE: Except where prohibited or restricted by law and notwithstanding the fact that the winner may be required to sign a separate Affidavit of Eligibility and Liability/Publicity Release, winner's acceptance of Prize constitutes winner's agreement and consent for Sponsor to use and/or publish the winner's full name, city and state of residence, Promotion entry, and/or statements made by winner regarding the Promotion or Sponsor, winner's voice, photographs and other likeness, worldwide and in perpetuity for any and all purposes, including, but not limited to, advertising, trade and/or promotion on behalf of Sponsor, in any and all forms of media, now known or hereafter devised, including, but not limited to, print, TV, radio, electronic, cable or World Wide Web, without further limitation, restriction, compensation, notice, review or approval.

MISCELLANEOUS: Entrants who do not follow all of the instructions, provide the required information in their entry form or the like, or abide by these Official Rules or other instructions of Sponsor may be disqualified. All Promotion entries become the property of Sponsor and will not be acknowledged or returned. Online entries will be considered to be entered by the authorized account holder of the e-mail address submitted at time of entry and he/she must comply with these Official Rules. The authorized account holder is deemed as the natural person who is assigned to an e-mail address by an Internet access provider, online service provider or other organization that is responsible for assigning e-mail addresses for the domain associated with the submitted e-mail address.

PRIVACY: Personal information collected by Sponsor will be used for administration of the Promotion and awarding of a Prize. In addition, by entering, entrants and/or winner agree to Sponsor's use of entrant's/winner's personal information as described in its Privacy Policy at Please refer to Sponsor's privacy policy for important information regarding the collection, use and disclosure of personal information by Sponsor.


DISCLAIMER: Promotion Parties are not responsible for printing or typographical errors in these Official Rules or in any Promotion-related materials. Sponsor reserves the right, in its sole discretion, to disqualify any individual that tampers with the entry process. Sponsor also reserves the right to terminate, suspend, cancel or modify the Promotion and award the Prize for the Promotion from among all eligible, non-suspect entries received (i) as of the date of termination or modification, as applicable, using the judging procedure outlined above and (ii) in a random drawing if for any reason this Promotion is not capable of running as planned due to any reason, including infection by computer virus, bugs, tampering, fraud, unauthorized intervention, technical failures or other causes that may corrupt or impair the integrity, fairness or proper play of the Promotion. Promotion Parties are not responsible or liable for any events which may cause errors and/or the Promotion to be stopped, including but not limited to any error, omission, interruption, deletion, defect, delay in operation or transmission, communications line failure, theft or destruction or unauthorized access to, or alteration of, entries, nor are they responsible for any problems or technical malfunction of any telephone, network or telephone lines, computer online systems, servers, or cable, satellite, or Internet Service Providers, computer equipment, mobile equipment, software or any other failure of any email or entry to be received by Sponsor on account of technical problems, human error or traffic congestion on the Internet or at any web site, or any combination thereof, including any injury or damage to entrant's or any other person's computer or mobile device relating to or resulting from participation in this Promotion or downloading any materials in this Promotion. Promotion Parties are not responsible for computer, mobile, mechanical, technical, electronic, network or other errors or problems, including any errors or problems that may occur in connection with the administration of the Promotion, the processing of entries, or in any other Promotion-related materials. The Promotion Parties may stop you from participating in this Promotion if you violate Official Rules or act, in Sponsor's sole discretion: (a) in a manner Sponsor determines to be not fair; (b) with an intent to annoy, threaten or harass any other entrant, winner or the Sponsor; or (c) in any other disruptive manner. Should more prizes be awarded through a computer, hardware, or software malfunction, error or failure, or for any other reason, in any prize category, than are stated for that category in the Official Rules, Sponsor reserves the right to award only the number of prizes stated in the Official Rules for that category. CAUTION: ANY ACT OR ATTEMPT BY AN ENTRANT TO DELIBERATELY DAMAGE ANY WEB SITE OR UNDERMINE THE LEGITIMATE OPERATION OF THIS PROMOTION IS A VIOLATION OF CRIMINAL AND CIVIL LAWS. SHOULD SUCH AN ATTEMPT BE MADE, PROMOTION PARTIES RESERVE THE RIGHT TO SEEK DAMAGES AND OTHER REMEDIES (INCLUDING ATTORNEYS' FEES) FROM ANY SUCH INDIVIDUAL(S) TO THE FULLEST EXTENT PERMITTED BY LAW.

WINNER LIST: Entrants are responsible for complying with these Official Rules. To receive the winner list for this Promotion, send a self-addressed stamped envelope to: Metis, 79 Madison Avenue, New York, NY 10016. Please reference the dates of the Promotion Period and Prize with your request.

SPONSOR: Kaplan, Inc.

Early Registration Deadline:

Are You Data Curious?

Experience 28 interactive data science talks from industry-leading speakers over 2 action-packed days.

DAY 1: JULY 24

For Aspiring Data Scientists

14 speakers will demystify data science and discuss the training, tools, and career path to the best job in the United States.

DAY 2: JULY 25

For Business Leaders, Managers & Practitioners

14 speakers will explain how data science applies to your work, what needs to be done to integrate data science into an organization, and how to achieve this integration.

The #DemystifyDS Experience

Demystifying Data Science is designed to be equal parts informative and interactive. All registrants will have access to the presentation recordings after the conference - but you have to attend live for the full experience!



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



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



Receive post-conference access to presentations.

Last year over 3,000 people attended from more than 100 countries. Here’s what some of them had to say:

“Loved the event and format.”

“This was a great virtual conference. I learned a LOT. I hope you have it again next year.”

“This conference was very informative. I’m very grateful you guys took the time to put it on!”

Meet The Speakers

Beth Comstock

Change Maker & Author | Former Vice Chair, GE

Beth Comstock is a change maker. Her mission is to understand what’s next, navigate change and help people and organizations do the same. By cultivating a habit of seeking out new ideas, people and places, she built a career path from storyteller to chief marketer to GE Vice Chair. In nearly three decades at GE, she led efforts to accelerate new growth and innovation, initiated GE's digital and clean-energy transformation, seeded new businesses and enhanced GE’s brand value and inventive culture. As President of Integrated Media at NBC Universal, Beth oversaw TV ad revenue and new digital efforts, including the early development of hulu.comBeth is a director at Nike, trustee of The National Geographic Society and former board president of the Cooper Hewitt Smithsonian National Design Museum. She graduated from the College of William and Mary with a degree in biology. Her first book, Imagine it Forward, is about summoning courage and creativity in the face of change and will be out September 18, 2018.

Lillian Pierson

CEO, Data-Mania LLC

Lillian Pierson, P.E. is a data strategist, trainer, and tech business coach who improves career prospects of tech professionals by teaching them the tools, principles, and practices they need to grow their brands and income. She advises SMEs and entrepreneurs on the data technologies, methods, and strategies that they can use to solve problems that their business faces. She is a licensed professional engineer, the founder of Data-Mania LLC, and the author of 3 technical books, the largest being Data Science for Dummies. She is also a course author to several data science courses for LinkedIn Learning. Since starting Data-Mania in 2013, she’s provided consulting services to numerous Fortune 500 companies.

Kirk Borne

Principal Data Scientist, Booz Allen Hamilton

Dr. Kirk Borne is a data scientist and astrophysicist who has used his talents at global technology and consulting firm Booz Allen Hamilton as an Executive Advisor and as the firm's Principal Data Scientist since 2015. In those roles, he focuses on applications of data science, data management, data mining, machine learning, and machine intelligence across a wide variety of disciplines. He also provides leadership and mentoring to multi-disciplinary teams of data scientists. Before coming to Booz Allen, Kirk was professor of astrophysics and computational science at George Mason University for 12 years, where he did research and taught students in the undergraduate data science and graduate computational informatics programs. Prior to that, Kirk spent nearly 20 years supporting data systems activities for NASA space science missions, including a role as NASA's Archive Project Scientist for the Hubble Space Telescope. Dr. Borne has a B.S. degree in Physics from LSU, and a Ph.D. in Astronomy from Caltech. He is an elected Fellow of the International Astrostatistics Association for his lifelong contributions to big data research in astronomy. Since 2013 he has been listed consistently each year as a top worldwide influencer in Big Data and Data Science on social media.

Mico Yuk

Chief Executive Officer, BI-Brainz Group | Author, Data Visualization for Dummies & More

Mico Yuk, Co-Founder/CEO, BI Brainz, Co-Founder of Analytics on Fire Community & Podcast, Founder, BI Dashboard Formula methodology, Author, Data Visualization for Dummies (Wiley), BI Advisor to the Fortune 500, Global Keynote Speaker, Named Top Analytics Blogger, SAP Mentor Alumni, Microsoft PASS Board Advisor, Formerly Founded, Xcelsius Gurus Network & To find out more about Mico, visit

Jake VanderPlas

Director of Open Software, University of Washington - eScience Institute

Jake VanderPlas is the Director of Open Software at the University of Washington’s eScience Institute, where his work focuses on data-intensive physical science research in an interdisciplinary setting. In the Python world, Jake is the author of the Python Data Science Handbook, and is active in maintaining and/or contributing to several well-known Python scientific computing packages, including Scikit-learn, Scipy, Matplotlib, Astropy, Altair, and others. He occasionally blogs on python-related topics at

Bob Hayes

President, Business Over Broadway

Bob Hayes is a researcher, writer, and consultant who likes to solve problems using the scientific method. His interests are at the intersection of customer experience, data science, and machine learning. 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.

Jennifer Prendki

Head of Data Science, Atlassian

Dr. Jennifer Prendki is the Head of Data Science at Atlassian, where she leads all Search and Machine Learning initiatives and is in charge of leveraging the massive amount of data collected by the company to load the suite of Atlassian products with smart features. She received her PhD in Particle Physics from University UPMC - La Sorbonne in 2009 and has since worked as a data scientist for many different industries. Prior to joining Atlassian, Jennifer was a Senior Data Science Manager in the Search team of Walmart eCommerce. She enjoys addressing both technical and non-technical audiences at conferences and sharing her knowledge and experience with aspiring data scientists.

Kamelia Aryafar

Vice President, Head of Data Science, Overstock

Kamelia Aryafar, Ph.D. is the Head of Machine Learning (ML), AI and Vice President and Head of Data Science at She leads a team of data scientists and machine learning engineers focused on building scalable ML/AI and computer vision tools to curate a personalized experience for Overstock users. Prior to Overstock she has been a Senior Machine Learning Scientist at Etsy for more than four years. Before Etsy, she was doing a Ph.D. in computer science and machine learning in Drexel University, building large-scale classification models.

Alex Vayner

Practice Leader, Data Science & Analytics, Capgemini North America

Alex Vayner leads Capgemini North America Data Science & Analytics practice.  Alex’s team works across all industries, driving the transformation of companies into insight-driven enterprises through the use of machine learning techniques, Artificial Intelligence and cognitive technologies. Alex has spent his entire career in data & analytics, with his last four roles focused on building and running high performance data science teams and capabilities in consulting and corporate environments.  Alex joined Capgemini from Equifax, where he served as VP, Global Data Innovation Leader, building a team responsible for pioneering disruptive data & analytics solutions for clients across all industries. Earlier in his career Alex held several analytics leadership roles in global management consultancies and public technology companies. Alex earned his bachelor’s degree in mathematics from University of Florida and his master’s degree in applied mathematics from Georgia Tech.

Claudia Perlich

Senior Data Scientist, Two Sigma

Claudia Perlich is a Senior Data Scientist at Two Sigma in New York City. Prior to her role at Two Sigma, she was the Chief Scientist at Dstillery where she designed, developed, analyzed, and optimized machine learning that drives digital advertising to prospective customers of brands. She started her career in Data Science 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 tends to be domain agnostic having worked on almost anything from Twitter, DNA, server logs, CRM data, web usage, breast cancer, movie ratings and many more. Perlich is still actively publishing, and has published over 50 scientific publications as well as a few patents in the area of machine learning. She received her PhD in Information Systems from the NYU Stern School of Business, and holds a Master of Computer Science from Colorado University.

Haile Owusu

Senior Vice President of Analytics, Decisions and Data Sciences, Turner Broadcasting

Haile Owusu is Senior Vice President of Analytics, Decisions and Data Sciences at Turner Broadcasting. Haile specializes in statistical learning as applied to forecasting and has a background in theoretical physics, including a PhD from Rutgers University, a Masters of Science from King's College, University of London and a B.A. from Yale University.

Carl Anderson

Director of Data Science, Weight Watchers

Carl is a hands-on senior data scientist, formerly leading data and data science at Warby Parker and WeWork. His career has taken him through a number of domains such as biology, politics, healthcare, robotics, architecture, and e-commerce. He is passionate about making organizations data-driven. In 2015, he published a book with O’Reilly entitled “Creating a Data-Driven Organization” which covers topics spanning data quality and cleaning, analytical skills, data visualization, and decision making. He blogs on data science, AI, and statistics at Medium,, and on twitter @leapingllamas.

William Ford

Director of Data Science, Chegg

William Ford is the Director of Data Science for Learning Services at Chegg.  Over the last two years at Chegg, he built a team that sits at the intersection of the Product, Business, and Engineering groups.  The team delivers insights and systems focused on improving business outcomes leveraging advanced analytics to support Chegg’s rapid growth. He got his start in distributed computational modeling in 2001.  In 2003, he shifted to Machine Learning/AI when he started graduate school at the California Institute of Technology where he ultimately received a PhD in Computation and Neural Systems. Before joining Chegg, he worked as a Data Science consultant and then led data science teams for multiple startups.

David Robinson

Chief Data Scientist, DataCamp

David Robinson is the Chief Data Scientist at DataCamp, where he guides analysis and research to help teach the next generation of data scientists. He has worked as a data scientist at Stack Overflow and received his PhD from Princeton University. He is the co-author with Julia Silge of the tidytext package and the O’Reilly book Text Mining with R. He is also the author of the broom, gganimate, and fuzzyjoin R packages and of the e-book Introduction to Empirical Bayes. He writes about R, statistics and education on his blog Variance Explained, as well as on Twitter as @drob.

Kate Strachnyi

Manager and Data Visualization Specialist, Deloitte

Kate Strachnyi is the author of Journey to Data Scientist; which is essentially compilation of interviews that Kate herself conducted with over 20 amazing data scientists. — with backgrounds ranging from LinkedIn and Pinterest to Bloomberg and IBM. She is also the creator of Humans of Data Science (HoDS) - a project that works on showing the human side of data science (housed on her Story by Data YouTube channel). Kate is a manager working for Deloitte, currently working in the data visualization & reporting space. She previously served as an insights strategy manager and research analyst, where she was responsible for enabling the exchange of information in an efficient and timely manner. Prior to working with data, she focused on risk management, governance, and regulatory response solutions for financial services organizations. Before joining the consulting world, she worked for the chief risk officer of a full-service commercial bank, where she was in charge of developing an ERM program, annual submission of ICAAP, and gap analysis of Basel II/III directives. Additionally, she worked as a business development associate at the Global Association of Risk Professionals (GARP). Kate received a bachelor of business administration in finance and investments from Baruch College, Zicklin School of Business. Certifications include Project Management Professional (PMP) and Tableau Desktop 10 Qualified Associate.

Follow Kate on Twitter: @StoryByData

Brent Dykes

Director, Data Strategy, Domo

Brent is the Director of Data Strategy at Domo and has 15 years of enterprise analytics experience at Omniture, Adobe, and Domo. He is a regular Forbes contributor on data-related topics and has published two books on digital analytics, including Web Analytics Action Hero. In 2016, Brent received the Most Influential Industry Contributor Award from the Digital Analytics Association (DAA). He has been a popular presenter at multiple conferences such as, Adtech, Pubcon, and Adobe Summit. Brent earned his MBA from Brigham Young University and his BBA (Marketing) degree from Simon Fraser University. Follow him on Twitter @analyticshero.

Naomi Keller

Executive Recruiter, BurtchWorks

An Executive Recruiter at Burtch Works, Naomi Keller began her career in marketing research, working with Knowledge Networks, Ipsos, and GfK. She then transitioned to the talent acquisition field, working within HR-technology as an account manager at LinkedIn and Yello, a start-up in Chicago. At Burtch Works, Naomi leads the data science recruiting team, working with companies ranging from Fortune 100 corporations to growing startups across the US, helping them to establish and grow their data science teams. Naomi's thorough knowledge of the quantitative community and the talent landscape give her a unique perspective when partnering with data science professionals and hiring authorities.

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 (MS '99, PhD '02), moved on to machine vision and machine learning at Sandia National Laboratories, then to predictive modeling of agriculture DuPont Pioneer, and cloud data science at Microsoft. Now at Facebook he works to get internet and electrical power to those in the world who don't have it, using deep learning and satellite imagery. 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.

Jerry Overton

Head of Industrialized Artificial Intelligence, DXC Technology

Jerry Overton is a data scientist in DXC Technology’s Analytics group. He leads the strategy and development for DXC's Industrialized AI offering. Jerry is the author of the O'Reilly Media eBook, Going Pro in Data Science: What It Takes to Succeed as a Professional Data Scientist. He teaches the Safari Live Online training course, "Mastering Data Science at Enterprise Scale: How to design and implement machine-learning solutions that improve your organization." In his blog, Doing Data Science, Jerry shares his experiences leading open research and transforming organizations using data science.

Ben Odom

Manager, Developer Evangelist Team, Intel

Ben Odom leads a team of fellow Developer Evangelists with Intel’s Developer Relations Division.  Currently Ben’s focus is on Artificial Intelligence, developing coursework for Intel’s AI Academy, and delivering workshops to University students and developers interested in how to take advantage of optimized frameworks and libraries on Intel architecture.  Previously Ben worked on Intel’s HTML5, Android and IOT developer outreach programs. Ben has a Masters Degree in Computer Science and Engineering from Oregon Health Sciences University.

Renée Teate

Data Scientist, HelioCampus

Renée M. P. Teate is the creator of the popular Becoming a Data Scientist Podcast and @becomingdatasci twitter account. She has worked with data for her entire career, from designing databases for small businesses to analyzing customer and alumni data for Rosetta Stone and James Madison University, to most recently developing predictive models and dashboards at Higher Ed startup HelioCampus as a Data Scientist. She has degrees from James Madison University and the University of Virginia, but has continued her own self-driven data science education online, and regularly speaks to others about learning Data Science.

Favio Vázquez

Principal Data Scientist, Oxxo

Favio Vázquez is making this world a better place step by step using AI, Data Science and helping others.

Vin Vashishta

Founder & Chief Data Scientist, V-Squared

Vin has 20+ years in tech (9 in data science & machine learning, 10+ in leadership). He has built products with revenue streams in the $100s of millions and saved companies just as much. He is a strategist for clients in the Fortune 100 to startups.

Sarah Nooravi

Marketing Analyst, MobilityWare

Sarah Nooravi is a lifelong learner and data geek. She has a history of delivering innovative marketing tools to help drive better business decisions in the entertainment and gaming industries at Operam and MobilityWare. She is also passionate about teaching and giving back to the community. In that spirit, she is teaching a DataViz Bootcamp through USC, she leads and coordinates monthly Machine Learning meetups at Ticketmaster, and she mentors aspiring data scientists and engineers. All of these activities support a core motivation for Sarah: helping set up others for success in industry.

Mark Meloon

Data Scientist, ServiceNow

Mark knows first-hand how difficult it can be to break into data science. With a degree in mathematics, not statistics or computer science, he was attempting to make a mid-career transition into the hottest field around. It was tough going at first: one tech recruiter even told him that he was “unemployable” as a data scientist and that she wouldn’t waste her time on him! But after a lot of research on job hunting techniques and painful trial-and-error, he was able to figure out how to crack the code to get hired. He now works in Silicon Valley as a data scientist at ServiceNow, officially “The fastest growing enterprise software company with more than $1 billion in revenue”. As part of his duties there, he interviews candidates for data scientist positions, giving him valuable experience on both sides of the interviewing table and unique insight into what companies are really looking for in applicants. He provides job seekers with the information they need to know to break into this data science on his website,

Safia Abdalla

Software Engineer, Tock; and Founder, Zarf

Safia works as a software engineer at Tock by day and is the solo founder of Zarf, an online marketplace for short-form fiction and non-fiction by night. In the past, she’s been a maintainer and collaborator in the Python open source data science space and an instructor of data science.

Randy Lao

Machine Learning Assistant, Data Application Lab

Randy works as a Data Science / Machine Learning Assistant in two data bootcamps: Trilogy Education (@ USC) and Data Application Lab. He also works at a nonprofit organization, IDEAS (International Data Engineering and Science Association), which is creating a data science learning platform to connect data science enthusiasts. Randy is a big supporter of this awesome data community and loves to contribute his resources to help others learn.

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.

Michael Galvin

Executive Director of Data Science Corporate Training, Metis

Michael comes to Metis from General Electric where he worked to establish their data science strategy and capabilities for field services and to build solutions supporting Global operations, risk, engineering, sales, and marketing. He also taught data science and machine learning for General Assembly. Prior to GE, Michael spent several years as a data scientist working on problems in credit modeling at Kabbage and corporate travel and procurement at TRX.

Michael holds a Bachelor's degree in Mathematics and a Master's degree in Computational Science and Engineering from the Georgia Institute of Technology where he also spent 3 years working on machine learning research problems related to computational biology and bioinformatics. Additionally, Michael spent 12 years in the United States Marine Corps where he held various leadership roles within aviation, logistics, and training units. In his spare time, he enjoys running, traveling, and reading.

Speaker Schedule

Sponsorship & Press Inquiries

Email us to learn about 2018 sponsorship opportunities or make press inquiries:

[email protected]