Kelsey Redman

AVP, Data Science at Comerica Bank

Kelsey Redman is a Data Scientist in the Enterprise Data & Analytics Group at Comerica Bank, a financial services company headquartered in Dallas, Texas. She has held that position since July 2017. In this position, Ms. Redman builds predictive models and runs experiments that focus on reducing attrition, generating revenue, and improving customer segmentation. Previously, she worked as a Statistician at Digital Matrix Systems, a consulting company that standardizes credit bureau information and creates customized credit score models for financial services clients.
Ms. Redman earned a Bachelor of Business Administration in Risk Management & Insurance, a Bachelor of Science in Statistical Science, and a Master of Science in Applied Statistics and Data Analytics from Southern Methodist University. She is a Certified Financial Risk Manager and a member of the American Statistical Association and Young Risk Professionals of Texas. She is currently pursuing her MBA at the University of Texas at Dallas.

Boryana Manz

Manager, Data Science at Capital One

Boryana Manz trained in the biomedical sciences during her PhD in Biophysics at UC Berkeley and post-doctoral fellowship at UCSF and CRI. She developed novel applications of data science in healthcare while at Parkland Center for Clinical Innovation at Dallas, TX. Currently she is a manager of data science in financial services at Capital One, Plano TX.

Dedy Kredo

Head of Customer Facing Data Science Organization at Explorium

Dedy leads the customer-facing data science organization at Explorium, enabling customers to deliver real business impact by discovering the most relevant data and features to supercharge their predictive models.

Prior to Explorium, Dedy held a number of product and leadership roles, the most recent was Co-Founder and Chief Product Officer of a big data analytics platform which enabled customers to radically simplify purchasing decisions and optimize online shopping experiences.

Dedy is an avid rock climber who is always on the lookout for the next big challenge.

Elizabeth Chabot

Lead Data Scientist at ScaleFactor

Elizabeth is a data scientist and researcher working at ScaleFactor, Inc. in Austin, TX. Elizabeth gained undergraduate degrees in Psychology, Neuroscience and Fine Arts from the University of Southern California and then went on to gain a Master's of Information and Data Science from the University of California, Berkeley. At ScaleFactor she is dedicated to creating software that allows small businesses to put their financial and scaling needs on autopilot. Outside of work Elizabeth is passionate about using data to connect people and raise awareness for causes that sometimes go overlooked in an age of information overload.

Darby Laffoon

Sr Manager – Big Data Platform Engineering at Charles Schwab

Darby Laffoon is a Senior Manager of Big Data Platform Engineering and Data Science Engineering at Charles Schwab. With 20 years experience in the tech sector, she has worked with teams across the IT spectrum, from web and app development to full scale technological transformation. She is a long time student of interpersonal communications and teambuilding, and taking on the challenge of turning around underperforming teams and processes is her true passion as a leader. Darby is located in Austin, Texas. She holds a BSPE in Sport Science from the University of Idaho and an MBA from Washington State University.

Alex Schwarm

VP/Head of Data Science at Dun & Bradstreet

Alex Schwarm, Ph.D., leads the Data Science team at Dun & Bradstreet focusing on Sales & Marketing Solutions as well as Supply Chain risk. He holds a Ph.D. in Chemical Engineering from Texas A&M University and has 30 U.S. patents in the areas of semiconductor manufacturing, solar cell manufacturing, marketing/sales targeting, and most recently in the area of novel natural language processing applications in marketing. He has held previous roles focusing on Product Management, Consulting, and Marketing. His current focus is in leveraging advancements in natural language processing and developing novel machine learning models to help optimize marketing and sales team performance.

Ilya Katsov

Head of Data Science at GridDynamics

Ilya Katsov is a Head of Data Science at Grid Dynamics. He joined Grid Dynamics in 2009, and since then has been leading engagements with a number of major retail and technology companies, focusing primarily on Big Data, Machine Learning, and Economic Modeling. He is currently leading the consulting practice that helps clients to become successful AI adopters and deliver innovate AI solutions. Prior to joining Grid Dynamics, Ilya worked at Intel Research on emerging wireless communication technologies. He is the author of several scientific articles and international patents, and also authored a book, “Introduction to Algorithmic Marketing: Artificial Intelligence for Marketing Operations” (2017).

Randi Ludwig

Sr. Manager, Applied Data Science at DELL

Randi R. Ludwig is a Data Scientist at Dell Technologies within Support and Deployment Services. She brings data science solutions to business problems involving tech support, warranties, and repairs on Dell products. She also focuses on raising visibility for data science at the executive level and connecting global Dell data scientists into a networked community that can collaborate and learn from one another. Additionally, she is a co-organizer of Women in Data Science ATX and promotes diversity and fostering a welcoming space for newcomers to the field. Before venturing into industry, Randi completed a PhD in Astrophysics at UT Austin, including research on both active galactic nuclei and how students learn astronomy, which gave her experience with varied statistical data-mining techniques and many kinds of data sets.

Meltem Ballan

Data Science Lead at GM

Meltem is an accomplished technology executive with a unique combination of analytical and leadership expertise developed over 20 years both in industry and academia. She co-founded a technology startup providing a Big-data analytics and ML platform. She has also managed large multinational and multidisciplinary projects in automotive, aviation, healthcare, software and marketing, as well as established labs, worked on academic projects, and authored over 30 publications on ML/AI implementation, analytics and neuroscience. She recently joined GM as a senior member of Chief Data and Analytics Office. During her career she has designed complex machine learning models and implemented AI projects including natural language processing (NLP), linear and logistic regression, supervised and unsupervised learning, neural network, deep learning algorithms and hybrid approaches of computer vision. Her passion for cognitive and biological bases of data prompted her to have a career in academia where she received a post graduate degree in Complex Systems and Brain Sciences with a minor in cognitive and behavioral neuroscience. She implemented her knowledge of neuroscience and analytics while a professor at the University of North Carolina Chapel Hill Medical School.

Ying Ding

Professor, School of Information and Dell Medical School at UT Austin

Dr. Ying Ding is Bill & Lewis Suit Professor at School of Information, University of Texas at Austin. Before that, she was a professor and director of graduate studies for data science program at School of Informatics, Computing, and Engineering at Indiana University. She has led the effort to develop the online data science graduate program for Indiana University. She also worked as a senior researcher at Department of Computer Science, University of Innsburck (Austria) and Free University of Amsterdam (the Netherlands). She has been involved in various NIH, NSF and European-Union funded projects. She has published 240+ papers in journals, conferences, and workshops, and served as the program committee member for 200+ international conferences. She is the co-editor of book series called Semantic Web Synthesis by Morgan & Claypool publisher, the co-editor-in-chief for Data Intelligence published by MIT Press and Chinese Academy of Sciences, and serves as the editorial board member for several top journals in Information Science and Semantic Web. She is the co-founder of Data2Discovery company advancing cutting edge AI technologies in drug discovery and healthcare. Her current research interests include data-driven science of science, AI in healthcare, Semantic Web, knowledge graph, data science, scholarly communication, and the application of Web technologies.

Amy Daali

Founder & CEO at Lucea AI

Dr. Amy Daali is the Founder and CEO of Lucea AI, a healthcare artificial intelligence company in San Antonio. We make Healthcare more Human by developing AI Models and putting Health Data into action. She is an Engineer, Entrepreneur and a multidisciplinary Data Scientist. She founded San Antonio Data Science Meetup and currently serves as the Chair of IEEE Engineering in Medicine and Biology Society (EMBS) and the organizer of Women in Machine Learning & Data Science Meetup.

Over the last 10 years, she held various roles in the industry and academia including Engineer at Southwest Research Institute (SWRI), Postdoc Research Fellow at University of Texas Health Science Center at San Antonio (UTHSCSA) and a Data Scientist at USAA.

She received her B.E degree in Electrical Engineering from the School of Electrical and Computer Engineering at the University of Minnesota and M.S., Ph.D. degrees in Electrical Engineering from the University of Texas.

Nancy Hornberger

Executive Vice President – Healthcare at ElectrifAi

Jesse Barbour

Chief Data Scientist at Q2ebanking

Jesse Barbour is the Chief Data Scientist at Q2ebanking. He uses machine learning to discover hidden structure, insight, and value from data. His work has paved the way for multiple ground-breaking products including Sentinel, Q2’s flagship security offering, and SMART, the company’s targeting and messaging platform. Jesse’s 10 years in the financial services industry have been driven by a relentless passion to deliver technologies that have a fundamental, positive impact on individuals and communities.

Moody Hadi

Group Manager - Financial Engineering at S&P Global Market Intelligence

Moody is a Senior Director of Financial Engineering at S&P Global – Market Intelligence. As a Group Manager in New Product Development within Market Intelligence, he leads a team focusing on applying modelling techniques, such as machine learning and data sciences to extract information value for risk management. Previously, he was Co-Head of Research and Development at Credit Market Analysis (CMA), where he lead the model development and research on Credit Default Swaps pricing and risk management. Prior to CMA, Moody was a Senior Quantitative Analyst at the Chicago Mercantile Exchange (CME) Group, where we worked on Over-The-Counter (OTC) Clearing of Interest Rate and Credit Derivatives and the SPAN Margining Algorithm. Prior to that he had several senior roles in analytical & technical consulting, spanning diverse areas from Asset-Liability Management (ALM) to Business Intelligence (BI).

Moody holds a Bachelors of Science in Computer Science from Georgia Institute of Technology, Masters of Science in Operations Research from Columbia University and MBA from the University of Chicago – Booth School of Business.

Fatih Akici

Manager, Risk Analytics and Data Science at Populus Financial Group

Fatih Akici is a Manager of Risk Analytics/Data Science at Populus Financial Group. From building machine learning models and software applications to coordinating their deployment and validation, as well as optimizing business processes; he has an extensive experience in applying data science in credit risk management space. Fatih oversees the company’s automation efforts in various facets of business. His collaboration with various teams led to impressive results in the joint initiatives. As a data-oriented strategic thinker with a background in mathematics, statistics, and economics; he always strives to create higher business value.

Seemit Sheth

Head of Data Science at Capital One

Seemit Sheth is a senior director and head of data science for Capital One Financial Services. Over the last 18 years, Seemit has built world class data science organizations for several lending businesses and developed multiple industry-leading data science products. He has been twice awarded Capital One’s top award from their CEO.

Prior to Capital One, Seemit worked as a research biostatistician at the eastern virginia medical school for one year with focus on survival analysis in oncology studies.

Seemit has Master’s degrees in both mathematics as well as statistics. He also has a bachelor’s degree in classic percussion music and plays indian drums, Tabla

Micah Price

Principal Associate Data Scientist at Capital One

Michael Zelenetz

Analytics Project Leader at New York-Presbyterian Hospital

Michael is a paramedic turned data scientist. He works on the Analytics team at New York Presbyterian where he focuses on using data science to improve operational efficiency and patient safety.

Priscilla Boyd

Senior Manager, Data Analytics at Siemens Mobility

Priscilla Nagashima Boyd is a Senior Manager of Data Analytics at Siemens Mobility based in Austin, TX. With expertise in transportation and machine learning, she leads a team of data scientists and developers that are seeking solutions for mobility problems through novel data science techniques and design thinking. With over 10 years of transportation experience as a practitioner, Priscilla has worked with public and private sectors in the Americas and Europe, advising on new technologies and related policy to deliver more efficient, accessible and sustainable transportation for urban communities. She has a Bachelor of Science in Computing and Information Systems from the University of London and a Master of Science in Software Engineering with emphasis in machine learning from the University of Oxford. She is also a STEM ambassador, the former honorary secretary of the Women in ITS (Intelligent Transportation Systems) UK and has acted as an evangelist for connected vehicles and big data during her TEDx talk in 2017.

Joe Ray

Data Science and Engineering at Dell

Joe Ray has been in the data science and analytics space for 13 years, and has led data science teams for the last 6 years. As a part of widely varied industries, he has seen up close and personally how data teams thrive. He brings this experience to bear at Data Science Salon by sharing lessons learned and practical advice on how to help data science succeed in an organization.

Raktim Saha

Director, Digital Insights at CGI

Mr. Raktim Saha is a Senior Advisor and Director with CGI Technology and Solutions Inc, he represents the Emerging Technology Practice business unit within CGI US. He specializes in Data and Analytics Product Development and modernization of Data Management practices.
Raktim has more than 20 years of experience with consulting and industry in developing Technology Strategy & Solutions, and leading Engineering & Analytics organizations towards Integrated Data Solutions and Data Products re-invention. Working with CGI’s customers, he is helping evangelize the transition of various industry patterns from traditional data warehousing to sophisticated Big Data Analytics driven culture and Big Data AI solutions, which has improved business process and customer engagement. Raktim has graduated from Florida International University on MIS and has an undergrad in Engineering from India, and he lives at North Austin with his wife and two teenage daughters.

Jacob Claussen

Manager, Analytics/Data Science at Zynga

Jacob Claussen has been at Zynga for the past three years, where his innovative work has redefined the role of data science in live-game operations. Past projects have focused on predictive modeling, deep learning, anomaly detection, segmentation, experimentation, simulation, recommendation, and optimization, among other -tion words. As a manager, he has continued to contribute to live operations while building growth and development opportunities for a team of top analytics talent.

Prior to starting at Zynga, Jacob completed his Physics PhD at The University of Texas at Austin, where his research focused on quantum physics/string theory.

Jordan Birdsell

Chief Machine Learning Architect at phData

With more than 10 years of experience launching successful Analytics and Data Science organizations at large enterprises, Jordan Birdsell now brings his expertise and knowledge to our clients around the globe. As head of machine learning services at phData, Jordan and his team help companies escape from the endless loop of machine learning POCs and move them into driving real value.

Peter Guerra

North America Chief Data Scientist at Accenture AI

Peter Guerra is the North America Chief Data Scientist in Accenture's AI practice. He is responsible for building the data science and AI business to help North American clients solve their toughest challenges leveraging innovative AI solutions. He has 15 years of experience in creating big data and data science/machine learning solutions for commercial businesses in Life Sciences, Retail, Energy, Transportation, Finance, and other sectors. He has also lead data science practices for US Federal government clients (Law Enforcement, DoD, Intelligence Community) where he was responsible for the architecture and implementation of one of the world’s largest data clusters for machine learning. He has had the privilege of speaking at numerous industry events, including NVIDIA GTC, Blackhat, Hadoop Summit, Strata+Hadoop, and more. He has earned a BA in English, BS in Computer Science from University of Maryland, an MBA from Loyola University, and is currently a PhD candidate in Artificial Intelligence at UMBC.

Dhruv Bhargava

VP Data Science at Square Panda

Over the past 14 years, Dhruv has focused on making data science and analytics the competitive advantage of the organizations where he's worked at. Most recently, he was the VP Data Science at Square Panda, creating adaptive learning algorithms to help children of ages 2-7 learn language and improve literacy outcomes. Previously, he led data science globally at Zynga and was the founding data scientist at leading CDP AgilOne where he created the core machine learning IP.

Raffael Marty

VP Research and Intelligence at Forcepoint

Raffael Marty is chief research and intelligence officer at Forcepoint. He brings more than 20 years of cybersecurity industry experience across engineering, analytics, research, and strategy to the company. Marty leads Forcepoint X-Labs, a specialized group that is dedicated to behavior-based security research and developing predictive intelligence to differentiate Forcepoint's human-centric product portfolio.

Prior to Forcepoint, Marty ran security analytics for Sophos, a leading endpoint and network security company, launched PixlCloud, a visual analytics platform, and Loggly, a cloud-based log management solution. Additionally, Marty held key roles at IBM Research, ArcSight and Splunk and is an expert on established best practices and emerging innovative trends in the big data and security analytics space. Marty is one of the industry's most respected authorities on security data analytics, big data and visualization. He is the author of Applied Security Visualization and is a frequent speaker at global academic and industry events.

Marty holds a master's degree in computer science from ETH Zurich, Switzerland and is a student of the Japanese tradition of Zen meditation.

Andy Terrel

President at NumFocus

Andy Terrel is a technical executive with multiple startup experiences implementing distributed, large data applications. In his previous academic research, he is known for creating novel algorithms to speed implementations of mathematical models on the world's largest supercomputers.

Andy received his Computer Science PhD at the University of Chicago in 2010. He has held research positions at Argonne National Lab, Sandia National Lab, Institute of Computational Engineering and Sciences at The University of Texas-Austin, and the Texas Advanced Computing Center. In industry, Andy served as lead developer at Kove, Inc. during its early stages, where he helped bring a record breaking SAN disk array to market. Andy also has also worked with Enthought, Inc and was part of the founding team at Continuum Analytics.

Andy is a passionate advocate for open source scientific codes. To this end, he is a board member of the NumFOCUS foundation and has been involved in the wider scientific Python community since 2006. Andy has contributed to numerous projects in the scientific stack and hopes push for data to become a first class object for scientists worldwide.

Linnette Attai

President at PlayWell LLC

Linnette Attai is the founder PlayWell, LLC, a global compliance consulting firm providing strategic guidance to companies and education institutions around the complex obligations governing data privacy, marketing, safety, and content. Linnette brings more than twenty-five years of experience to the work, advising on data protection and marketing regulations, developing policy and compliant monetization models, managing incident response communications, and building organizational cultures of compliance. She also serves as virtual chief privacy officer and General Data Protection Regulation (GDPR) data protection officer to a range of organizations. Linnette is a recognized expert in the youth and education sectors and speaks nationally on data privacy. She is a TEDx speaker and author of the books, “Student Data Privacy: Building a School Compliance Program” and “Protecting Student Data Privacy: Classroom Fundamentals.”

Alyssa Simpson Rochwerger

VP, Data and AI at Appen

Alyssa is a customer-driven leader dedicated to building AI products and solutions that delight customers, bring new value to market, and solve difficult challenges. Her experience in scaling AI products from conception to large-scale ROI has been proven at both startups and large enterprises alike. As Director of Product Management at IBM Watson, Alyssa saw first-hand how thoughtful, sophisticated use of data has the power to transform industries. During her tenure at IBM, she oversaw the development of a large portfolio of AI products including vision, speech, emotional intelligence and machine translation. Alyssa was born and raised in San Francisco and holds a BA in American Studies from Trinity College. When she is not geeking out on data and technology, she can be found hiking, cooking, and dining at “off the beaten path” restaurants with her labradoodle, Scout.

Chris Lindner

Product Science Manager at Indeed

Chris Lindner is a Product Science Manager at Indeed, the world’s #1 job site. He became a professional data scientist in 2014, and has conducted hundreds of interviews of data science job candidates and sifted through countless resumes. Chris is also a PhD astrophysicist and semi-professional poker player.

Eero Laaksonen

CEO at Valohai

Eero is a San Francisco based startup founder and CEO. Their company Valohai focuses on large-scale, in-production machine learning and deep learning tooling. Eero is a frequent speaker in ML events around the world.

Caitlin Hudon

Lead Data Scientist at OnlineMedEd

Caitlin Hudon is lead data scientist at OnlineMedEd. She's spent the past decade doing applied analytics, mostly focused on collecting, analyzing, and visualizing data to make data products and guide strategic direction for startups, universities, non-profits, and other businesses. She is a co-founder of R-Ladies Austin, a sometimes-blogger at caitlinhudon.com, and an active member of the data science community. Find her on twitter at @beeonaposy.

Patrick McGarry

Head of Strategic Partnerships at data.world

Patrick has worked to build community and foster Open Source ideals at companies like Sourceforge/Slashdot, Alcatel-Lucent, and Perforce. Most recently Patrick served as the Director of Community for the Ceph open source project at the startup 'Inktank,' and later for Red Hat after a successful acquisition. Patrick enthusiastically helps companies to understand and adopt Open Source ideals through community engagement, conferences, and events. A seasoned speaker, Patrick has presented talks and workshops around the globe, including events like Linuxcon, OSCON, DEVIEW, OpenStack Summit, and a number of targeted custom events.

Gerald Fahner

Analytic Science-Senior Principal Scientist at FICO

Dr. Gerald Fahner is Senior Principal Scientist in FICO's Scores division where he is responsible for scientific research. He specializes on innovative methods and algorithms that turn data and domain knowledge into superior insights, predictions, and decisions. Gerald is also responsible for the core algorithms underlying FICO's Scorecard development platform. His work on causal modelling won the Best Paper award at the Credit Scoring and Credit Control XI conference, was awarded patents and made it into products. He also won a Best Paper award at the Data Analytics 2018 conference for developing practical methods in explainable artificial intelligence and transparent machine learning which are applied to boost the effectiveness of FICO’s credit risk score developments.

Prior to joining FICO in 1996, he served as a researcher in artificial intelligence, neural networks and robotics at the International Computer Science Institute in Berkeley and he earned his Computer Science doctorate from University of Bonn.

Marcelo Casas

SVP Data Science at GM Financial

Marcelo Casas is a Senior Vice President at GM Financial where he leads the Data Science Team. His team is responsible for predictive models and optimization solutions for different business areas across the company. In particular, the team’s work in pricing sensitivity and forecast market dynamics have transformed how GM vehicles are priced in the wholesale market.

Marcelo holds a Licenciado degree in Economics from Universidad Nacional del Sur, Argentina as well as a Masters in Economics from Boston College with specialization in Time Series and Micro-Econometrics. After teaching Econometrics for several years in his home country of Argentina, Marcelo returned to the US where he has worked for the last 10 years on advanced analytics applied to the auto-finance industry with Ally Financial, Ford Credit and GM Financial.