Our faculty are successful practice leads and technical leads on data analysis, data science, and business design teams at both top-tier organizations and high-growth start-ups. They share a passion for working with data to make their organizations and customers more successful, and a commitment to helping prepare the next generation of data analysts. You will benefit from working closely with them to solve real-world business problems.
Andy Catlin, Director, MS in Data Analytics and Visualization
Andy Catlin is a serial entrepreneur in data analytics and data science who has co-founded several successful start-ups, including Citigate Hudson (a custom advanced analytics provider now known as twentysix New York), Metrics Reporting (a company that provides job performance data to employers), and Mad Dog Data Science (a provider of process-oriented data for companies). He has led teams that have built analytics applications for the National Football League and several NFL teams, as well as international banks like Donaldson, Lufkin & Jenrette and ABN AMRO, and other global iconic organizations including Microsoft, Reuters, and Bloomberg.
Javier Guillen, Data & Artificial Intelligence Technology Specialist
Javier Guillen is a data & artificial intelligence technology specialist for one of the largest software companies in the world. He has 19 years of experience working in technology, data strategy and analytics and has participated in numerous deployments of corporate data & analytics initiatives involving reporting, governance, engineering and data science. Javier co-founded the Charlotte Business Intelligence User Group, a non-profit dedicated to promote Big Data and analytics education and professional networking in the US southeast region."
Jeffrey Nieman, Data Scientist, Ford Motor Company
An expert in operations, project management, and data analysis, Jeff Nieman has decades of experience wrangling, analyzing and visualizing data for major corporations including Cru Global, Cisco, and Ford Motor Company. He has also taught programming in the graduate data analytics program at the City University of New York School of Professional Studies. Jeff has a B.S. in Chemical Engineering from the University of Michigan, and an M.S. in Data Science from the City University of New York.
Joy Payton, Data Scientist, Educator, and Engineer, Children’s Hospital of Philadelphia
Joy Payton supports researchers in mastering the tools of reproducible, computational research. She is an expert in curriculum development and web design. Joy has a B.A. in Applied Mathematics from Agnes College, and an M.S. in Data Science from the City University of New York. She has also done advanced graduate work at Pennsylvania State University, and Comillas Pontifical University in Madrid.
Jessica Prue Rifkind, Director Strategic Initiatives at Audible, an Amazon Company
Jessica Prue Rifkind is a successful data scientist and management consultant. In addition to her work at Audible.com and for various Boston Consulting Group clients, Jessica has extensive volunteer experience. She has a Magna Cum Laude B.S. in Applied Economics and Management from Cornell, a Master of Public Administration from Syracuse University, and a Master of Business Administration from Columbia Business School.
Samuel Strum, Director - Data Technology, Customer Office at Prudential Financial
Sam Strum has been a data management and analytics leader at Prudential, Pfizer, Polo Ralph Lauren, and AT&T. He is also a serious guitar player, and a volunteer softball coach. He has a B.S. in Electrical Engineering from Lafayette College, and an M.S. in Information Systems from Drexel University.
Gary Sztajnman, Product Data Scientist, Verizon
Gary Sztajnman builds data products for Verizon. In his previous work for an A.I. startup, Gary developed an application that learns musical taste to ensure that music composition is customized for each user. Gary has also won several hackathons! Gary has an M.S. in Data Science from Columbia University, and an Master of International Business specializing in Information and Communications Technology from Paris Dauphine University.
James Topor, Managing Director, Mirus Global Advisory Services
James Topor combines his dual background in data scientist and management consulting in his role as a business advisor and financier. James has a B.S. in Computer Science from Eastern Connecticut State University, an M.S. in Computer Science from Virginia Tech, an M.B.A. in International Business from George Washington University, and an M.S. in Data Science from the City University of New York.
Jeff Wunderman, Data Science Engineer and Research Engineer, Hedge Fund
Jeff Wunderman works at a hedge fund in Jupiter Florida, and loves coding Python in Jupyter notebooks. He has also worked extensively as a professional performance and studio musician. His volunteer experience includes working as a children’s advocate in the Florida court system. Jeff has a B.S. in Computational and Applied Mathematics from the University of Central Florida, and a B.S. in Music, Finance, and Business Law from the University of Miami.
To ensure that you will gain the most in-demand skills, our curriculum was created with guidance from leaders in data-driven industries.
Daniel First, Data Scientist, QuantumBlack
Daniel graduated from Yale University with a B.A. in Cognitive Science and Neuroscience. After college, he completed a Philosophy degree at the University of Cambridge before transitioning into Columbia's M.S. program in Data Science. He then joined McKinsey & Company, first as a Management Consultant and then later as a Data Scientist at QuantumBlack, a machine learning subsidiary of McKinsey. In his work, he specializes in machine learning algorithms that can extract patterns from healthcare data. He has also published on the impact of AI on society.
Joe Manto, Former VP of IT, National Football League
Joe was an agent of change at the NFL for over thirty years, bringing the most advanced technologies to every aspect of the game. He was responsible for creating an integrated league-wide network, salary cap/contract analysis, real-time game play-by-play and statistics, integrating game video with data for instant analysis, and an advanced electronic medical records system that follows the player throughout his NFL career. Joe joined DARI Motion Analytics in 2015 as an exclusive sales agent to the NFL for their marker-less motion capture and analysis product. He is also a member of the RockDaisy Advisory Board.
Jeffrey Nieman, Data Scientist, Ford Motor Company
An expert in operations, project management, and data analysis, Jeff Nieman has decades of experience wrangling, analyzing and visualizing data for major corporations including Cru Global, Cisco, and Ford Motor Company. He has also taught programming in the graduate data analytics program at the City University of New York School of Professional Studies.
G. Thomas Perrone, Executive Director, JP Morgan Chase
Tom Perrone is an expert at analyzing data and helping businesses anticipate and solve problems. He has spent nearly three decades in technology management leadership positions at JP Morgan Chase, where he has worked for finance, technology, and application delivery departments within areas such as investment banking, custody services, and global trade services. During his time at JPM, Perrone has worked on some of the most strategic systems at the bank, enabling the business to manage a large portfolio and its leaders to make smart business decisions.
Thomas Quintana, Director of Enhanced Application Development, Voyant
Thomas is a software architect with over ten years’ experience in fast-paced startup environments and the Open Source Community. Previously he was Chief Technology Officer at Better Voice, where he worked on using Deep Learning with neural networks for speech recognition. Thomas is a data science enthusiast and is active in the developer community in Ft. Lauderdale as organizer and speaker of the Machine Learning Meetup Groups.
Chris Tanck, Co-Founder RockDaisy
Chris has deep expertise in data visualization and analytics, and in helping sports teams use data analysis to improve their performance at the gate and on the field. Prior to co-founding RockDaisy, he designed and developed the National Football League’s first big data analytics platform to inform on-field statistics, player contracts, salary cap modeling, ticket sales, digital media sales, and for optimizing athletic performance,. That solution, used by each of the NFL’s 32 franchises, also powers the statistics and graphics packages used in NFL broadcasts. Since co-founding RockDaisy, he has worked with sports franchises in professional football and hockey. He has also helped leaders of SMBs and data publishers make better and more informed business decisions. Chris has presented at NFL league ownership meetings and was a featured presenter at the 2014 MIT Sports Analytics conference.