Greg Green is Senior Instructional Professor and Director of the MS in Applied Data Science Program at the University of Chicago, and Senior Director for Industrial Partnerships and Strategy at the Data Science Institute. Dr. Green helps the University of Chicago professional data science students learn to apply data science to solve complex industry problems with greater impact.

Dr. Green is reshaping the content and approaches used to educate the next generation of professional data scientists at the University of Chicago.  Additionally, Greg is designing new, creative offerings more deeply connected to MS and PhD research programs in Data Science, Computer Science, Statistics, and Financial Mathematics. New course offerings developed and launched since joining the University of Chicago include an innovative approach to “Leadership in Data Science and Artificial Intelligence”, “Consulting in Data Science” and “Your Career in Data Science”.

Throughout his professional career, Greg has used his expertise in digital strategies, business analytics, and new product development to drive rapid revenue growth and accelerate business transformation. His previous work bringing innovation to an academic environment included authoring a Marketing Analytics course, designing a pre-requisite applied statistics course and serving as a lecturer for Marketing Analytics at Northwestern University.

Greg’s industry roles include Chief Analytics Officer at Harland Clarke Holdings, Director at Google, EVP/Managing Director at Publicis Groupe, and Analytics Practice Lead at PwC. Greg’s patented cloud-based media analytics platform was highlighted in Harvard Business Review and Fast Company.

Greg holds a Doctor of Philosophy in Mathematics from Claremont Graduate School and a Master of Science in Statistics from Michigan State University. Born in Owosso, Michigan, Greg is married to Jill, an artist, and their adult children include two more artists, a teacher, and an engineer. Greg and his family enjoy snowboarding, snow/water skiing and live theatre—as well as good food and friendships. Their passion for the environment is reflected in a love for Lake Michigan where they like to spend as much of the summer as possible.

Dr. Arnab Bose is Chief Scientific Officer at Abzooba, a data analytics company. He is a twenty-year industry veteran focused on machine learning and deep learning models for unstructured and structured data. Arnab has extensive industry experience in using data to influence behavioral outcomes in healthcare, retail, finance, and automated vehicle control.

Arnab is an avid writer and has published numerous papers for conferences and academic journals, as well as book chapters. He enjoys public speaking and has given talks on data analytics at universities and industry conferences in the US, Australia, and India. He serves on the board of the financial engineering graduate program at University of Southern California. Arnab holds MS and PhD degrees in electrical engineering from University of Southern California and a BS in electrical engineering from the Indian Institute of Technology at Kharagpur, India.

“Shaddy Abado is a Lead Data Scientist at Ulta Beauty where he focuses on developing machine learning models to optimize marketing strategies and enhance personalized experiences. With a background in engineering, throughout his career, Shaddy’s interests span various fields ranging from researching light-fluid interactions for aero-optics applications, developing data driven solutions for equipment predictive maintenance, and consulting companies throughout their digital transformation. Shaddy is passionate about teaching and engaging students in insightful education. Since 2012, he has been instructing graduate level courses in various academic programs.

Currently, Shaddy is a lecturer at the University of Chicago Master of Science in Analytics. He holds three US patents, has presented his research at national conferences, and has published papers in peer-reviewed journals and conference proceedings. Shaddy holds a PhD in aerospace and mechanical engineering from the University of Notre Dame.”

Gizem Aydin, PhD is an expert in data analytics, machine learning, and transformation with a passion for mentoring. With 15+ years of interdisciplinary academic and industry experience, her latest work is in manufacturing, pricing, logistics, and supply chain. She has received the CEO Award and Outstanding Achievement in Analytics awards for her contributions to Caterpillar.

Dr. Aydin teaches Principles of Data Mining, Python for Analytics, Supply Chain Optimization, Capstone courses and advises students. She holds a PhD and MSc in Industrial Engineering from University of Oklahoma, and BSc in IE and a BSc in CE from Cankaya University, Turkiye. She was a visiting scholar at the Kuhne Logistics University (Hamburg, Germany) and at the Technical University of Vienna (Vienna, Austria).

Abid Ali has worked in data and analytics for many years at various large organizations. He has designed, architected, and delivered many large-scale data transformations and migrations projects around the world in various countries such as US, UK, EMEA, and APAC. He has worked with many large enterprises across industries such as banking, insurance, retail, telecom, travel, consumer packaged goods, and manufacturing. In his work, he works closely with various levels of stakeholders of the organization from c-suite executives to the engineers. He provides strategic direction and guidance to these companies and makes them successful on their data and analytics journeys. He is experienced in various technologies, industries, and methodologies. Over the years, he has managed large portfolios of customer accounts from a million to tens of millions of dollars.

Ali believes in life-long learning and has acquired several advanced degrees and certifications over the years such as undergraduate in computer sciences, master’s in computer sciences (business intelligence and data warehousing), another master’s in information and knowledge strategy, an EMBA, a Ph.D. in organizational leadership, and several certifications from Teradata, Celonis, SAFe Agile, Azure, AWS, and Dataiku. Ali believes in giving back, sharing, and contributing knowledge and therefore teaches in top-tier universities in addition to his day job.

Francisco Azeredo is a financial economist and decision scientist with eleven years of experience working for leading financial and consulting firms in the Chicago area. He is presently a senior vice-president at Northern Trust, working on research and development of quantitative strategies for fixed income and equities at Northern Trust Asset Management.

Prior to joining asset management, Francisco led strategic and quantitative driven projects across Northern Trust’s three major business units. His experience included leading analytics projects on foreign exchange global revenue forecast, wealth management client deposit modeling, wealth management digital client behavior modeling, treasury deposit modeling, derivatives and hedging solutions and foreign exchange high-frequency algorithmic execution cost. He also conducted research on foreign exchange algorithmic execution methods and securities lending price modeling.

His prior work experience includes credit risk, operational risk and macroeconomic modeling for stress testing and capital planning, analysis of complex financial instruments, interest rate modeling, and econometric and predictive analysis for litigation matters involving financial institutions and multinational corporations.

His research in financial economics was recognized by leading economists in the Handbook of the Equity Risk Premium, Intermediate Financial Theory, and an encyclopedia of behavior economics. He currently teaches reinforcement learning, statistical analysis, non-linear statistical modeling, and optimization methods in the MSc Analytics at the University of Chicago and has five years of prior experience teaching at Northwestern University, the University of California, Santa Barbara and Riverside. He holds a PhD in Economics from the University of California, Santa Barbara.

Dr. Balasanov is Chief Data Officer at Quiet Light Securities L.L.C. He has been a financial industry practitioner for more than 20 years, working at leading financial institutions, like Bank of America, Chicago Research and Trading, Ritchie Capital and other trading and asset management companies. His roles include leading data-driven quantitative research divisions, trading, and risk management. Dr. Balasanov is an Academic Advisor at FTI Consulting, and a member of Advisory Committee for project “Developing a Deep Learning-Computer Vision Framework to Monitor Avian Interactions with Solar Energy Facility Infrastructure,” for the U.S. Department of Energy.

Dr. Balasanov earned his Master of Science degree in Applied Mathematics and Ph.D. in Probability Theory and Mathematical Statistics from the Lomonosov Moscow State University, Russia, where he studied under Andrey Kolmogorov and leading members of his school. His primary expertise and research interests are in the areas of stochastic modeling, advanced data analysis and AI, digital transformation, risk evaluation and decision making.

Yuri Balasanov has taught at Graduate Program on Financial Mathematics (MSFM) and Graduate Program on Analytics (MScA) at the University of Chicago since 1997. The list of courses on his curriculum includes Fixed Income Derivatives, Mathematical Market Microstructure, Linear and Nonlinear Statistical Analysis, Machine Learning, Bayesian Methods, Advanced Machine Learning and AI, Real Time Analysis, Robotics, Financial Analytics. Dr. Balasanov has provided training for the industry, including FRB Chicago, FRB Philadelphia, PwC, Chicago Trading Company, and other organizations.

“Stephen Barry serves as technology and data leader at a global investment bank. He brings more than 25 years of leadership experience in the realms of technology and finance. Furthermore, Stephen’s expertise extends to data science and AI, with a demonstrated proficiency in platforms like AWS, Azure, and GCP.

Stephen is currently a Lecturer in the Master’s in Applied Data Science at the University of Chicago. He graduated with a master’s degree from the same program in 2020. His background in finance and technology, has been pivotal in applying data science in practical contexts.

Complementing his professional experience, Stephen served as a Teaching Assistant in the same University of Chicago Master’s program for three years for multiple courses including: BDP, DEPA, ML, and Data Visualization. This role allowed him to bridge the gap between academic knowledge and its application in the finance and tech industries. Steve is an enthusiastic lifelong learner that provides him unique perspective to communicate complex concepts clearly.”

Shree Bharadwaj works at West Monroe, a management consulting company. As the AI Center of Excellence lead for M&A, he advises private equity and venture capital firms and C-level executives on value creation, post-close synergies, and data and analytics (BI/AI) strategies focused on business outcomes. In his previous executive leadership roles at Syndigo and IRI, he led the product ownership, data strategy, data science, next-gen platform and M&A integrations. His expertise revolves around growth and innovation, leadership and operational excellence. Additionally, his focus revolve around automation and driving decisioning using AI/ML, data engineering at scale using on-premise and cloud platforms, effective data visualizations, model-driven design, and algorithimic thinking.

Bharadwaj was elected to the Global Standards Architecture Board at GS1, where he worked with global industry leaders to develop standards, road maps, and governance and compliance requirements relating to food services, healthcare, retail, supply chain, and CPG/FMCG verticals. His experience spans across multiple industries that include AdTech, EdTech, Fintech, healthcare, MarTech, public safety, retail, and telecom in organizations that range from startups to Fortune 100 companies. His interests include His interests include Intelligent Systems and Robotics, Machine Learning at scale, Data Engineering, Data Visualization & Knowledge Engineering.

Sanjay Boddhu is the Head of AI/ML Engineering at HERE Technologies, a global leader in location data and platform services. He has over 15 years of experience in leading and mentoring diverse and distributed teams in developing state-of-the-art applications and solutions in the domains of Computer Vision, Image Processing, Natural Language Processing, Predictive Analytics, and Data Science Strategy/Modeling. He holds a Ph.D. in Computer Science and Engineering from Wright State University and is a Senior Member of the IEEE.

At HERE, he is leading the UniMap Automation initiative, which leverages AI and machine learning to transform raw spatial and nonspatial data from various sources, such as imagery, probe data, car camera feeds, lidar, and IoT data, into an actionable, navigable digital map that is updated in near real-time. He is also responsible for designing and deploying algorithms at scale, managing product roadmaps and stakeholder engagements, and driving innovation and excellence in map automation and computer vision. His mission is to revolutionize how maps are created and maintained, and to enable new use cases and opportunities for autonomous and robotic mobility.

Anil Chaturvedi has over 35 years of professional experience at companies such as AT&T Bell Labs, Kraft Foods, Capital One, and Accenture. He has provided consulting services to Bank of America, Fannie Mae, Johnson & Johnson, and Procter & Gamble. His general research interests include enhancing business value using data science. He has patented and published advanced algorithms for predictive modeling, market segmentation, new product development, product positioning, customer loyalty, consumer promotion mix optimization, and brand strategy. He earned his PhD from Rutgers University and an MBA from IIM Ahmedabad, India.

Shahbaz Chaudhary has over fifteen years of experience developing software systems for financial companies, specializing, most recently, in trading systems. His free and open-source tools are widely used on Wall Street. Three years ago, he made the switch to data science. He graduated from the University of Chicago’s Master of Science in Analytics program, where his team won top honors for their capstone project. He is currently working at Charles Schwab as a manager of data science.

Brian Craft is a data scientist with ten years of industry experience. He is currently a Business and Marketing Data Scientist at Google, where he focuses on building models to analyze creative ad effectiveness. Previously he worked as a Principal Data Scientist at Conagra Brands, where he focused on demand forecasting, and as a Data Scientist at Cars.com where he developed models around vehicle churn and pricing. He holds a BA in Economics and a MS in Data Science with a focus on Computational Methods from DePaul University.

Mark Hendricks is an Associate Senior Instructional Professor in the Department of Mathematics and as the Director of Financial Mathematics, he manages all aspects of the program. His industry experience includes quantitative research, systematic trading, risk management, for hedge funds and asset managers. Mark also has been a consultant and adviser for firms in trading, private equity, and data analysis.

Mark has taught courses, reviews, and workshops at the graduate level for Financial Math, the Booth School of Business, and the Department of Economics. He has taught portfolio and risk management, asset pricing, valuation, and data analysis, among other things. Mark’s courses emphasize active learning with application and data.

As a Ph.D. candidate for Financial Economics at the University of Chicago’s Booth School and Department of Economics, Mark won awards including a Stevanovich Fellowship and Lee Prize. Mark holds an M.A. in Economics and a B.S. in Mathematics.

Nick Kadochnikov is an Associate Clinical Professor at University of Chicago Data Science Institute as well as head of Artificial Intelligence and Advanced Technology group at Harbor Global, where he is at the forefront of creating cutting-edge Generative AI tools and advanced tech solutions. These innovative capabilities assist law firms and corporate legal teams in enhancing their service quality, making legal processes more streamlined, accessible, and requiring less manual effort.

Before joining Harbor, Nick served as a Director of AI at William Blair, where he oversaw the development of advanced AI/ML capabilities and intelligent workflows to transform Investment Banking processes. Prior to that, Nick dedicated 20 years at IBM, successfully crafting AI solutions for a wide range of enterprise functions such as supply-chain, sales, marketing, finance, procurement, and legal. In his final role at IBM Watson Health Consulting, his main focus was on utilizing AI to address healthcare challenges, enhancing patient outcomes, elevating population health, and optimizing the efficiency of clinical trials.

I am a full-stack data scientist, software developer, and educator with diverse backgrounds. I have thirty years of experience in applying data science in commercial software development, property and casualty insurance, and retail financial service industries. I specialize in algorithm development with an emphasis on statistical learning, machine learning, and artificial intelligence.

I co-published the book “Using Data Analysis to Improve Student Learning: Toward 100% Proficiency” in 2006. I published the e-book “A Practitioner’s Guide to Machine Learning” in 2020.

I received my Ph.D. in statistics from the University of Chicago.

Sebastien Donation has nearly two decades of experience in the fields of high-performance computing, software design and development, and financial computing. Currently an architect in Bloomberg Office of the CTO, he has a wide variety of professional experience, including serving as CTO of a FX/Crypto trading shop, head of software engineering at HC Technologies, quantitative trading strategy software developer at Sun Trading, partner at high-frequency trading hedge fund AienTech, and a technological leader in creating operating systems for the Department of Defense. He also has research experience with Bull, and as an IT Credit Risk Manager with Société Générale in France.

Sebastien has taught various computer science and financial engineering courses over the past fifteen years at a variety of academic institutions, including the University of Versailles, Columbia University’s Fu Foundation School of Engineering and Applied Science, University of Chicago and NYU Tandon School of Engineering. Courses taught include: Computer Architecture, Parallel Architecture, Operating Systems, Machine Learning, Advanced Programming, Real-time Smart Systems, Computing for Finance in Python, and Advanced Computing for Finance. Sebastien holds a PhD in High Performance Computing Optimization, an MBA in Finance and Management, and an MSc in Analytics from the University of Chicago. His main passion is technology, but he is also a scuba diving instructor and an experienced rock-climber.

Natural Language Processing

Ignas Grabauskas is a Data Scientist at Simpson, Thacher, & Bartlett, a premier law firm well-known for its expertise in financial and corporate law. Ignas has over five years of experience applying machine learning and deep learning techniques to the finance and legal domains. His recent work includes using LLMs for various tasks such as document classification, customized named-entity recognition (NER), and summarization. Ignas holds a BA in Physics from the University of Chicago and is an alumnus of the MS in Applied Data Science program.

Bayesian Methods SP24

Wendy Klusendorf has over twenty years of experience in manufacturing, supply chain, and procurement. She graduated from the University of Chicago Master of Science in Analytics program in 2016 and has been working for the university since 2017. She currently works as the Strategic Sourcing Director at Sabert Corporation in Chicago.

Machine Learning SP24

Dr. Justin Kurland is the Principal Data Scientist at Northwestern Mutual, leading machine learning initiatives across the organization. Justin’s 20+ years in data and analytics include a senior lectureship in the Department of Computer Science at the University of Waikato, 50+ peer-reviewed publications, and numerous open-source contributions in Machine Learning and Times Series forecasting. With degrees from Rutgers University, Boston University, and University College London, Justin also has extensive data science consulting experience working with organizations like Microsoft and the UK Home Office.

Roger is the CEO and Managing Director at NLITX. NLITX uses data and analytics to solve strategic problems. Roger also currently is a Lecturer at the University of Chicago. He teaches Leadership Skills in the Master of Science in Analytics Program. Previously Roger was VP, Analytics and Customer Operations at Entytle. Entytle provides a SaaS tool supporting customer installed base automated sales with AI and machine learning. Roger has also worked at Gartner, Sagence, Booz & Co, PwC, Diamond Management & Technology Partners and the Boston Consulting Group. Roger is active in the data, analytics and technology communities in the Chicago area. He attends many MeetUps, roundtables and industry events. Roger founded and chairs the Chicago Booth Big Data & Analytics Roundtable.

Mrs. Mei Najim has been providing advanced analytics consulting services to the property and casualty insurance industry since 2018, with over fifteen years of hands-on analytics experience in the industry. Since 2007, she has been mainly leading and working on various predictive analytics and data science projects to develop advanced analytics capability. She also has extensive statistics, machine learning, and data mining experience dealing with large and complex data sets.

She has been a frequent speaker at various industry conferences to share her expertise in predictive analytics, machine learning, and data science. She holds a BS in actuarial science from Hunan University and two MS degrees in applied mathematics and in statistics, from Washington State University. Najim is a member of the American Statistical Association and a Certified Specialist in Predictive Analytics (CSPA) of the Casualty Actuarial Society.

Danny Ng is a Director of Machine Learning at Expedia Group. At Expedia, one of the world’s leading travel companies, Danny leads a team of scientists on developing machine learning models for travel search experience. Danny is also an Adjunct Lecturer at the University of Chicago where he teaches graduate courses for the Master of Science in Applied Data Science program. Danny earned his PhD in Statistics from the University of Chicago.

Dr. Pamuksuz, a professor of AI, specializes in applied mathematics, machine/deep learning, responsible and generative AI. He has contributed to various analytics journals, including IEEE Transactions on Artificial Intelligence, and has shared his insights at several national and international conferences.

Since joining the University of Chicago as a faculty member in 2018, Dr. Pamuksuz has taught a range of subjects, including data mining, machine learning, and linear & non-linear models, along with more specialized areas like AI-data science for leaders and Generative AI Research. His supervision of capstone theses has often centered on computer vision and natural language processing.

In the professional realm, Dr. Pamuksuz has an impressive record. He has led data science teams at several Fortune 500 companies, provided expert consultancy in architecting cloud-based machine learning solutions, and co-founded Inference Analytics in 2018. Under his leadership, Inference Analytics was recognized in 2023 as one of the top Machine Learning Companies in Illinois, marking a significant milestone in healthcare analytics in Chicago.

Dr. Pamuksuz’s academic path has taken him through some of Illinois’ most prestigious universities. He completed his MS in Computer Engineering/Science at Northwestern University and went on to earn his Ph.D. from UIUC. Today, he contributes his expertise as a faculty member at the University of Chicago. This journey, connecting three significant academic institutions, reflects a strong foundation and dedication to his field and a deep engagement with the state’s rich educational landscape. Outside of his professional endeavors, Dr. Pamuksuz is enthusiastic about hackathons, not only participating in several but also organizing them twice annually since 2020. His involvement has yielded notable success in various data challenges. As a sports fan, he follows Champions League Soccer, supporting Galatasaray, and enjoys engaging in basketball and volleyball during his leisure time. He also enjoys smooth/gypsy jazz where you can find him on Wednesdays in his favorite place Green Mill.

“Over more than 30 years, Don has served in a variety of assignments that utilize research and data analysis to provide impact to major CPG, Retail and Foodservice companies. Don currently serves Assistant Clinical Professor at the University of Chicago, Previously Don served as Board President of Chicago Chapter of the American Statistical Association and as Program Director of the MS,Business Analytics program at DePaul University. As Senior VP, Analytics for HAVI Group, Don helped pioneer new analytics implementations for McDonald’s and Coca-Cola. Prior to joining HAVI Group, Don was Director of Advertising Analytics for Sears, Roebuck & Co. – bringing cutting edge analytics of Sears’ media (tv, radio, print) support to drive ROI based decision making. Don has also managed research and analytics for several major brands for Kraft Foods and site location analytics and modeling for Hallmark Cards.

Don was also an active duty U.S. Army officer for 11 years – serving in troop leadership positions in South Korea, Germany and the U.S. Don graduated from the United States Military Academy at West Point with a BS in Engineering. Additionally, he has an MSE in Operations Research from The University of Texas at Austin and MBA from the University of Kansas.”

Dr. Nalini Polavarapu has been with Bayer for over ten years and leads data science strategy for a global team of analytical and IT professionals, specialized in machine learning, operations research, and cloud analytics to deliver better products to market faster through data science. Nalini also serves as the senior leader on the Data Science Center of Excellence Council. Over the course of her career, she has initiated multiple external partnerships and collaborations with start-ups, large corporations, and universities. She was the first data scientist at Monsanto and played a key role in building its world-class global data science program. Nalini has a PhD and dual MSc in computer science and bioinformatics from the Georgia Institute of Technology in Atlanta. Nalini has authored and co-authored several analytical patents, research articles in leading scientific journals, as well as book chapters on high throughput data analysis and applications.

Ashish Pujari is a Data and AI consultant, practitioner, and educator with over 20 years of experience in in machine learning, big data, and cloud computing. He has led large global technology and data science teams and consulted for Fortune 500 companies in banking, finance, healthcare, insurance, and manufacturing.

As a Principal ML/AI Architect at AWS, Ashish provides strategic guidance to enterprise customers on leveraging the cloud for AI and Machine Learning. Prior to joining Amazon, he served in various technology leadership roles at Credera, GLG, IRI, and Pegasystems. Ashish holds a Master of Science in Analytics from the University of Chicago and BS in Electrical Engineering from the National Institute of Technology, Rourkela.

Jenny Schmidt, founder of J Schmidt Consulting, is an expert in developing analytics talent. As an experienced leadership and career coach, Jenny works with those seeking to enter the analytics field and analytics professionals to advance in their careers, get their ideas implemented, develop executive presence, and perform at a high level. She also partners with analytics leaders and HR executives to develop analytics talent and facilitates team-building workshops to improve the productivity and effectiveness of analytics teams. Jenny is an expert panelist for the International Institute for Analytics (IIA) and a founder of the Des Moines Data & Analytics Meetup, a networking group for data and analytics professionals.

Supply Chain

Dr. Jeanette Shutay is currently the President and Chief Data Officer at Shutay Consulting. Jeanette is a strategic research and data science leader with extensive experience building and scaling advanced analytics and data science teams. Her analytical expertise spans across product, sales, marketing, supply chain, and operations. Jeanette also has approximately 10 years of consulting experience working with nonprofit organizations, educational institutions, and the federal government. As a consultant, Jeanette focuses on data strategy, research methodology and analysis, as well as campaign and program evaluation. Jeanette is incredibly passionate about nature and wildlife, and she tries to find ways to incorporate her skills to help improve the environment and the lives of all creatures that inhabit the Earth.

Big Data & Cloud Computing

Jonathan Williams has been working in statistical consulting and data science education for fourteen years and currently teaches full-time at the University of Chicago. Previously, he managed data science teams at Civis Analytics, working on behalf of public sector clients, and before that he worked as a vice president at Compass Lexecon, providing and supporting expert reports and expert testimony for litigation. Jonathan earned his BA and MS degrees in statistics from the University of Chicago (’07, ’08) and is also an alumni of the Master of Science in Analytics program (’16). His focuses include regression analysis, data visualization, technical writing, financial valuation, mortgage portfolio modeling, and damages estimation.

Michael Xiao has held senior leadership roles in data science, analytics, product management, and data organizations in the healthcare, fintech, and insurance industries, where he has successfully built and scaled several large organizations. His teams have developed and successfully deployed a variety of innovative machine learning and data science solutions. He has also previously worked in various roles including financial forecasting, pricing, product management, and project management.

He is a Fellow of the Society of Actuaries, holds a Bachelor’s degree from Dartmouth College, and completed his MBA with honors at the University of Chicago Booth School of Business. Areas of interest for him include product management and AI adoption and change management, computer vision, and model interpretability and explainability.

PhD in Theoretical Physics, MS in Computer Science. Currently – Applied Scientist at Amazon. Previous jobs: Computational Scientist at the Argonne National Laboratory, Scientist at LIGO project of California Institute of Technology. I specialize in scientific computing, HPC, machine learning, data analysis.

Time Series SP24

Fan Yang is an experienced professional in the financial industry, blending over a decade of expertise in data science and financial modeling with a background in consumer banking. Specializing in Deposits, Residential Loans, Auto Loans, and Credit Cards. His journey has been marked by contributions to loss forecasting, marketing analytics, card acquisition model development, and credit data management. Currently serving as a Senior Manager at Discover Financial Service in Chicago, where he leads the Card Acquisition Risk Modeling team, overseeing both onshore and offshore operations. His role involves building machine learning models and providing strategic data-driven support for various business needs.

His professional narrative also includes tenures at BMO, where he led the Marketing Advanced Data Analytics team, and KeyBank/Northern Trust, focusing on Comprehensive Capital Analysis and Review (CCAR) and Current Expected Credit Loss (CECL) Stress Tests. In these roles, he used advanced quantitative techniques XGBoost, and Convolutional neural network (CNN), helping companies drive business growth and optimize risk management strategies effectively. Fan’s educational background includes a Ph.D. in Statistics and an MBA from the University of Iowa. He currently teaches Time Series Analysis and Forecasting at the University of Chicago and has three years of prior experience teaching at the University of Iowa.

Jose Alvarado serves as the Assistant Director of Enrollment Management for the MS in Applied Data Science program. Prior to his current role, Jose served as a higher education professional specializing in recruitment and enrollment management. He has worked at great institutions around the Chicagoland area like the University of Illinois Systems, Northwestern University, and Loyola University Chicago. He brings with him extensive knowledge working with undergraduate, graduate, and international student populations.

Josie Badillo Sittig currently holds the role of Assistant Director of Marketing/Advertising & Communications for the MS in Applied Data Science program. With an extensive background exclusively in the advertising agency realm, Josie brings a wealth of experience gained from collaborating with diverse clients, spanning healthcare to lottery sectors. Prior to stepping into her current position, Josie’s career has been marked by a dedication to delivering impactful marketing and communications solutions.

Kristin I. McCann, PhD serves as the Chief of Staff, Executive Director for the Master’s in Applied Data Science program. Her interdisciplinary research and practice centers on how institutions can best support historically underrepresented and underserved student and faculty populations in academia—specifically in STEM and academic medicine contexts. Prior to her current role, she served Associate Dean of Students for The University of Chicago’s National Institutes of Health-funded Medical Scientist Training Program which MD-PhD pathways. Dr. McCann completed her postdoctoral fellowship with  Northwestern University’s Feinberg School of Medicine where she conducted research on pathways to careers in medicine for low-income and racially underrepresented youth.

Daniel Truesdale serves as an enrollment advisor for the MS in Applied Data Science in-person and online programs. A graduate from the Harris School of Public Policy at the University of Chicago, Daniel has been assisting students on their educational journey and encourages lifelong learning. He has also completed Machine Learning and Data Engineering courses at the University of Chicago, which enables him to understand the University’s commitment to Data Science.