Jonathan H. Owen is Chief Scientist for Operations Research and Advanced Analytics at General Motors and Director of the GM R&D Operations Research (O.R.) Lab. A 19-year GM veteran, Owen leads strategic innovation activities for applied O.R. and advanced analytics across diverse areas of the business that includes pricing and revenue management, portfolio planning, vehicle technology selection and content optimization, supply chain and logistics, market demand modeling, and dealer effectiveness. Owen earned his Ph.D. in IE/MS at Northwestern University and graduated from the General Management Program at Harvard Business School. Owen has served on the Analytics Certification Board and as the INFORMS VP of Practice. He represents GM in several external forums and is a member of the IE/MS Advisory Board at Northwestern University.
Joe Miscavige has more than ten years of experience in the digital space. Currently, Joe is the Director of Analytics within the Business Intelligence Group at PBS, where he is responsible for providing actionable, data-driven insights about children’s media and education throughout the organization. Prior to joining PBS, Joe managed cross-network advanced platform analysis for AMC Networks. He is a co-leader of the Digital Analytics Association, Washington D.C. chapter and the DAA’s Practitioner of the Year for 2018. Joe holds a Master of Science in Library & Information Science from Long Island University and a Bachelor of Arts in Public Relations from Susquehanna University. Follow him on Twitter at @joemiscavige to learn all of the secrets.
Andre de Waal received his Ph.D. in theoretical computer science from the University of Bristol during 1994. He spent the next year in Germany and Belgium continuing his research in Logic Programming and Automated Theorem Proving. During 1996 he returned to South Africa to take up his position as lecturer at the School of Computer Science and Information Systems at North-West University, where he was later promoted to Associate Professor. During 1999 he became one of the founding members of the Centre for Business Mathematics and Informatics at the same university. He became responsible for the Data Mining Program in the Centre and shifted his research focus to include Neural Networks and Predictive Modeling. He joined SAS Institute in Cary, NC during December 2010 to take up the position of Analytical Consultant in the Global Academic Program.
Jamie Wheeler is a Senior Lead Data Strategist at Booz Allen Hamilton in the Strategic Innovation Group with over 20 years of professional experience. His background includes data analytics, deep understanding of technical impacts upon business operations, economics, engineering and project leadership, change management moving to data-driven cultures, and ability to communicate ideas between technical and non-technical interests. He holds degrees in engineering, business and economics.
Wheeler’s work currently focuses on standing up advanced analytics capabilities and data strategy advising major operations in the federal space. Additionally, he leads efforts in deep learning focusing on applications in demand forecasting, image processing and unknown threat identification using combinations of existing data, synthesized data and data fusions.
He enjoys shaping the thought-space around data science and the social applications and economic and business benefits from applying advanced analytics. He believes that advanced analytics can meaningfully, powerfully and effectively augment the worker and their efforts.
As Director of Analytics at Express Oil Change & Tire Engineers, Mills provides actionable insights to the senior leadership team, including the CEO, and has designed and automated numerous reports used to support company operations. Some of the tools he specializes in include Microsoft SQL Server, SSRS, R, and Tableau. Mills holds a Master of Business Administration in Business Analytics, Master of Science in Marketing, and Bachelor of Science in Marketing from The University of Alabama.
Jacob Hummel has a Ph.D. in computational astrophysics from the University of Texas, where he studied the formation of the very first stars in the Universe by running massive supercomputer simulations. Generating insight required sifting through the many terabytes of data, and he now applies those same computational and analytic skills to e-commerce data in a quest to understand the desires and intentions of Overstock.com’s customer base. As a member of the core machine learning team, he does so by helping build scalable machine learning, natural language processing, deep learning and computer vision tools to curate a personalized experience for Overstock users.
Joshua Jones is CEO of StrategyWise, a Birmingham-based Data Science Consulting form. As a founding partner, Jones has recruited talent from Harvard, Columbia, Accenture, IBM and NASA while building a global portfolio of big data clients including Fortune 500 companies like Southern Company, Toshiba, Samsung and Chick-Fil-A.
Jones’s career experience has spanned six startups, 40 countries, and seven languages. He has been quoted by Forbes, CIO.com, the Atlanta Business Chronicle and Entrepreneur Magazine, and is a regular speaker and lecturer in universities and conferences across the U.S. In 2016, Birmingham Business Journal named StrategyWise the Fastest Growing Business in Birmingham.
Jones received his Master of Business Administration at Emory University’s Goizueta Business School and his Bachelor of Science in Business Administration from the University of Alabama
Centers for Disease Control and Prevention Dr. Brian Gurbaxani is both an engineer and a molecular and computational biologist by training. He currently works as a health scientist in the Office of the Associate Director for Science at the Centers for Disease Control and Prevention. After earning a bachelor’s degree in engineering physics from Cornell University, he worked for 11 years as a systems engineer in the Southern California aerospace industry. A Ph.D. in molecular biology from UCLA with an emphasis on immunology, mathematical modeling and bioinformatics brought him to the CDC to work as a computational biologist and statistician. He now works as the lead technical liaison between Georgia Tech (and other universities) and the CDC, arranging projects that bring the latest engineering technologies to bear on problems in public health. Gurbaxani is also an adjunct professor in the H. Milton Stewart School of Industrial and Systems engineering (ISyE) and in the department of electrical and computer engineering (ECE) at Georgia Tech, where he has been involved in training both undergrad and graduate students for the last 14 years.
Nate Ravitz was named Vice President, Audience Development, in March of 2017.
In this role, he manages ESPN’s industry-leading app and web experiences, including programming of the ESPN App & ESPN.com, audience development and performance analytics, multiplatform visual content and design, mobile alerts, Fantasy and Insider content, and emerging coverage areas.
Ravitz joined ESPN in 2007. He served the company as a general editor of ESPN Fantasy, a hybrid role of editor/writer/on-air talent for fantasy content. He was elevated to deputy editor in 2008, where he oversaw all aspects of ESPN Fantasy content for ESPN.com, including integration across platforms. In 2011, he was promoted to senior director of fantasy and premium content, adding Insider content and business strategy to his role. In 2014, he led the development of ESPN Now while adding responsibility for ESPN-branded social media. In 2015, he assumed the role of senior director, digital video and push operations, where he added digital video curation and distribution for ESPN digital properties and led the launch of ESPN on Snapchat Discover. Most recently, Ravitz oversaw programming of content strategy for all social media channels for ESPN’s major brands and sports verticals including Facebook, Twitter, Instagram, Snapchat, and YouTube.
Operations Research has a long and influential presence in GM. As early as the 1950s, GM employed analytical techniques for transportation science and traffic flow analyses. In the 1980s, GM used mathematical optimization methods to reduce logistics costs and improve assembly line job sequencing. In the 1990s, it used mathematical modeling to improve manufacturing throughout and patterned warranty cost reduction analyses after epidemiology studies from the health care field. Near the turn of the century, GM applied decision analysis to determine the best business model for its OnStar™ technology and service. More recently, Operations Research activities were centralized within the R&D Organization, continuing to employ a scientific approach in thinking about and attempting to understand problems and implement viable solutions to current problems and future opportunities. In this presentation, we describe several recent O.R. and analytics initiatives through the lens of automotive revenue management. We provide a high-level overview of key decisions over time, along with illustrating examples that motivate the core analysis capabilities required to support.
Too often, analytics are a last-minute addition to the development cycle of a website or a mobile app. This can lead to poor implementation, inconsistent modeling, and unusable data post-launch. In this talk, Joe will walk you through a recent product lifecycle at PBS where analytics were present at every single stage of development, how that positively affected the project, and what lessons were learned that could be applied to future projects
Thirty years ago, “spreadsheets” was a skill one listed as a high-tech job, along with “word processing.” Today, these skills are a foregone conclusion for any professional – we are surprised finding out anyone cannot use Excel, Word, or their Google counterparts. Thirty years ago, these staples of today changed the borders of what was technology, finance and accounting, and turned those tasks into a skill every person should have. In 30 years, we have made portions of skilled jobs mundane through intelligent application of technology.
It will not be 30 years until the same happens with machine learning. The demand for machine learning is growing, as is the capability of every user to do it. Machine learning is still the light at the end of the tunnel – it is powerful, flexible and offers tremendous insight – but if machine learning is the light, then deep learning is the train.
New technologies are not automatically adopted, even if we believe in their power. Cultures, embedded practices and non-business motivations impede implementation if not respected and addressed. With this rate of change in technology, we must do better in how we implement them to achieve buy-in and operationalize our efforts.
Express Oil Change & Tire Engineers has delivered record setting growth that leverages industry-leading analytics including operational KPIs, customer behavior analysis, data integration, and reporting tools. John Mills will lead a presentation covering the company’s data-driven culture and some of the tools and insights that have attributed to the company’s ability to achieve its vision as “the pre-eminent automotive maintenance provider, leading our industry through excellence, innovation, and growth.”
In this talk we will explore the applications of different facets of AI (machine learning, deep learning, NLP and computer vision) in online retail and e-commerce. We will walk through practical examples of how AI can be used to personalize customer experience and revolutionize your customer journey through personalized marketing campaigns, personalized recommendations, supply chain, CRM, reranked search and more. Hummel will share his thoughts on building successful AI teams and an experiment-driven culture that will reshape your business by enhancing customer experience through AI.
While study, research and lectures may do a good job of priming you for a career in data science, practicing data science in the enterprise is often an eye-opening experience. In this talk, StrategyWise CEO Joshua Jones will share insights from the front lines; from dealing with corporate politics to deploying algorithms at a large scale. Learn how to go beyond the numbers and ensure you are fully prepared to survive in the wild world of corporate data science.
In 2013, high-level meetings between the CDC and the Georgia Institute of Technology resulted in a push to implement new engineering methods and technologies to solve public health challenges. A focus of this collaboration has centered on Industrial and Systems Engineering (ISyE), as many public health problems have or should have a large element of classic operations research methodology, which many CDC epidemiologists and field workers are not trained in. Problems with logistics, supply chains, resource optimization, and big data analytics in many parts of the CDC have never been dealt with as such, and are often handled ad hoc, by intuition, or not explicitly at all. This often results in excessive costs, over the deployment of personnel, or missed project targets such as percent of the population tested or vaccinated. The CDC has leveraged this collaboration to address public health challenges such as the optimal use of possibly infected organs for transplant, optimizing forward and reverse cold chains for vaccine campaigns in low resource settings, contact tracing on airlines, model building, and calibration to fight Ebola, malaria, and HIV, optimal deployment of personnel and resources domestically, transport of vaccines in the Remote Marshall Islands, and many other challenges.
Millions of sports fans rely on ESPN’s digital products to deliver news, highlights, analysis, storytelling, live-streaming video and so much more. Managing a vast inventory of content to meet the expectations of fans with infinite combinations of interests is a challenge ESPN embraces. Ravitz will discuss how his team uses data and analytics to create the best possible experiences for fans on multiple platforms and devices while also driving against core business objectives. The presentation will include specific examples of tools used to make a variety of decisions, from strategic all the way through real-time programming.