Dr. Michael Bradley

Professor and Department Chair, Data Science & Analytics, Merrimack College

Dr. Bradley is a Professor and Chair of the Department of Data Science and Analytics at Merrimack College. He holds a Ph.D. in mathematics from the University of Notre Dame and a B.A. in mathematics from Merrimack College.

Dr. Bradley’s areas of interest include data science, the history of mathematics, math education, and sports statistics. His book series Pioneers in Mathematics profiles the life and work of 50 famous mathematicians. He has written journal articles and undergraduate textbooks about discrete mathematics, calculus, and precalculus. He recently taught courses in Basic Statistics with Fantasy Football, Discrete Mathematics, Differential Equations, and Foundations of Data Science I.

Dr. Andrew Banasiewicz

Professor of Practice and Director of Graduate Data Science & Analytics Programs

Dr. Andrew Banasiewicz is a Professor of Practice and the Director of graduate Data Science & Analytics programs at Merrimack College.  He is also an active analytic consultant specializing in executive risk modeling and analysis. A career statistical analyst and researcher, prior to embarking on an academic and consulting career Professor Banasiewicz spent nearly two decades as an industry practitioner working with marketing, risk management and insurance organizations, progressing from Senior Analyst to Senior Vice President of Analytics and Director of Data Science.

As an academician, Dr. Banasiewicz held full-time faculty appointments at the University of Wyoming and Boston University; he also served as a visiting professor at numerous US and foreign institutions including Harvard University, Audencia Ecole de Management (France), Tribhuvan University (Nepal) and Bandung Institute of Technology (Indonesia). He authored more than a dozen of peer-reviewed journal articles and more than two dozen of conference papers, including several that won ‘best paper’ awards, and he is currently working on his 6th book; he is also a fellow of several research and professional organizations, and a frequent speaker at conferences in the Americas, Europe, Asia, Africa and Australia.

Professor Banasiewicz’s primary area of expertise is the development of custom, data-intensive decision support systems encompassing predictive modeling, text mining, and impact measurement; his research interests are focused on evidence-based decision-making, data-driven organizational learning, and data science and analytics curriculum design. Dr. Banasiewicz teaches the Data Science Capstone and Business Analytics Capstone courses for the Merrimack Data Science & Analytics programs.

Dr. Fotios Kokkotos

Associate Professor of Practice, Data Science & Analytics

Dr. Fotios Kokkotos is an accredited professional statistician (PStat®) by the American Statistical Association with over 25 years of experience in statistical consulting. Dr. Kokkotos specializes in the analysis of massive and complex databases using advanced data science and statistical techniques. He has a wide range of experience in many areas of statistics and data science, including but not limited to data mining, predictive analytics, deep learning, economic modeling of patient health outcomes, and is also an expert in Medicare data.

Dr. Kokkotos is a long-time member of the American Statistical Association and the Mathematical Association of America and holds a doctorate degree in mathematical statistics from The American University in Washington DC, a master’s degree in applied statistics and a bachelor’s degree in mathematics, both obtained from Wright State University, in Dayton, Ohio.

His current research interests are the application of statistics, data mining and statistical computing, and Dr. Kokkotos is an author and reviewer of numerous articles and poster presentations in many scientific journals, conferences and academic institutions.  He has been involved in many statistical research collaborations with colleagues from top universities, such as Harvard, Cornell, Tufts, Michigan and Northwestern.  Fotios teaches Foundations of Statistical AnalysisPredictive Modeling, and Healthcare Analytics Capstone for the Data Science & Analytics program.

Joanna Blanchard, Ph.D.

Associate Professor of Practice, Data Science & Analytics

As a Faculty member of Merrimack College, Dr. Blanchard is driven by possibilities for students through this program.  Data Science is applicable in all industries and it is constantly evolving as new applications and new learning opportunities continue to be discovered. She believes strongly that those who gain an education in Data Science can enter career pathways in many different fields such as sports analytics, insurance, finance, hospitality, and retail, just to name a few, and they can be assured that their education will be in-demand.

Dr. Blanchard has presented at multiple conferences and has also authored several research studies.  She holds her undergraduate degree in Chemical Engineering from the University of Colorado-Boulder, and her Ph.D. from the Massachusetts Institute of Technology. She also has earned her master’s degree in Data Science from Merrimack College.  She teaches Foundations of Data Science I for the Data Science program.

Michelle Allen, M.S.

Adjunct Faculty Member, Data Science & Analytics

Michelle is an accomplished executive leader who has managed various global organizations, large-scale vendor contracts and systems implementations in technology, pharma and health care.  Professionally certified in Six Sigma and Project Management, Michelle holds her B.S. degree in Industrial Technology Engineering at Rhode Island College and an advanced degree in Engineering and Operations Management at the University of New Haven.

As an adjunct Professor at Merrimack College, Michelle designs and teaches the graduate level course, U.S. Healthcare Ecosystem.

Yuchun Regina Chang, Ph.D.

Adjunct Faculty Member, Data Science & Analytics

Dr. Chang has over 25 years of experience in strategic analytics.  She is the analytic lead of the CPG and Insurance vertical at Epsilon.  Her interests and responsibilities involve the design and management of data driven marketing analytics that help clients optimize results across customer lifecycle, including data and insights, orchestrated multi-channel multivariate test design, measurement and attribution, segmentation, predictive modeling, and strategic applications of analytic outcomes – using little data and big data.  Regina also consults regularly with clients on best practices and other guidance around evolving their analytic capabilities.

Dr. Chang holds a B.A. of Sociology from National Taiwan University, and a master and Ph.D. degree in Consumer Economics from the Ohio State University.  She spoke at LIMRA Big Data Analytics Conference on leveraging big data to drive improved marketing outcomes.  As an adjunct faculty member with the Data Science & Analytics program, Regina is the instructor for our Data Exploration and Predictive/Prescriptive Analytics courses.

Andrew Klein, M.S.P.

Data Scientist, Clear; Adjunct Faculty Member, Data Science & Analytics

Andrew Klein is a Data Scientist with 10 years of experience in the field. He currently is a Data Scientist at Clear. He has also previously worked for Fulcrum Analytics, & Agilex Technologies, and the New York Yankees. He holds both a Master’s in Statistics in 2015 and a Bachelor’s of Science in Statistics & Information Systems in 2011 from Carnegie Mellon University. Andrew’s professional website is https://www.quantifyingmylife.com/ where he blogs about using statistics and visualizations to analyze social data. Andrew has been teaching Data Visualization for the Data Science & Analytics program since 2018.

Peter Salemi, Ph.D.

Adjunct Faculty, Data Science & Analytics

Dr. Peter Salemi has over 10 years of experience in quantitative research, machine learning, and statistics in both academic and industry settings. As a data scientist at The MITRE Corporation, he works with several Federal agencies ranging from the United States Department of Veterans Affairs to the Centers for Medicare & Medicaid Services. Dr. Salemi received his Ph.D. in Operations Research from Northwestern University, an M.S. in Operations Research from the University of California, Berkeley, and a B.S. in Mathematics and B.B.A. in Finance from the University of Massachusetts, Amherst.

His academic research interests lie at the intersection of machine learning and stochastic simulation, and Dr. Salemi’s research has been published in Operations Research, ACM Transactions on Modeling and Computer Simulation, and Journal of Simulation. Dr. Salemi has also served as the co-chair of the Simulation Optimization track for the 2017, 2019, and 2020 Winter Simulation Conferences, and as a reviewer for several academic journals.  His teaching interests are machine learning, data management, and statistics. As an adjunct faculty member at Merrimack College, Dr. Salemi is the instructor for both the Machine Learning and Foundations of Data Management courses.

Abhijit Sanyal, Ph.D.

Sr. Advisor, Spinnaker Technologies; Adjunct Faculty Member, Data Science & Analytics

Dr. Sanyal has extensive experience in data science, machine learning, high-end analytics and marketing strategy within the retail, financial services, telecommunications, pharmaceuticals and other industries. He is currently a senior advisor with Spinnaker Technologies and a Principal with SP Analytics LLC. He has conducted over 400 projects while also having deep coding expertise in creating solution driven insights independently and with teams using SAS, SQL, R and Python as well as extensive knowledge of cloud based big data technologies.

Dr. Sanyal has an undergraduate degree in Electrical Engineering from I.I.T (Kharagpur), an MBA from I.I.M (Calcutta) and a Ph.D. (Marketing) from the University of Massachusetts at Amherst. He is currently working on two books on “Exploring Data with R” and “Customer Valuation using R and Python” which are expected in 2021.  Abhijit is currently teaching our Data Visualization, Fundamentals of Data Management, and Data Exploration courses.

Bryan Shepherd, Ph.D.

Adjunct Faculty Member, Data Science & Analytics

Dr. Bryan Shepherd has over 15 years of experience in quantitative research, predictive analytics, and statistical programming across a variety of academic and industry settings.

Much of Bryan’s industry-side career has been in marketing research. As a Senior Data Scientist at an e-commerce startup in Durham, NC, Bryan developed statistical models that helped improve clients’ ROI and contributed to a successful exit when the organization was purchased in 2018. Prior to this he built segmentations and predictive models at the renowned market research company, Yankelovich.

Bryan has also worked in statistical software development and government contracting. At SAS Institute, Bryan helped validate the accuracy of components within JMP. While at RTI, Bryan helped build statistical models used by the National Center for Education Statistics (NCES) to understand and predict the behavior of NCES sample members. He served on RTI’s institute-wide Big Data/Data Science steering committee when it was formed in 2013.

As the principal at Chanalytics Research, Dr. Shepherd provided analytic solutions to clients ranging from large-multinational companies to small, one-person shops. These consulting engagements covered topics as varied as piracy off the east coast of Africa and wine price forecasting.

In addition to this industry experience, Bryan’s research has been published in academic journals and edited texts. He has taught research methods courses at both traditional, post secondary institutions and in online settings.

Dr. Shepherd has extensive experience in R, SPSS, and SAS, but these days most often works with the Python Data Science stack.

Carmen Taglienti, M.S.

Adjunct Faculty Member, Data Science & Analytics

Carmen has over twenty years’ experience as a Software Engineer and Systems Architect. He is a recognized leader in the Analytics, Large-Scale DBMS, Data Warehousing and the “Big Data” space.  Currently Carmen leads up Global Analytics and Data Architecture for Pearson as the company transitions from a book publishing company to a data-driven digital education organization. Prior to Pearson, Carmen built and led the Information and Analytics Practice for Slalom in Boston, which focused on working with clients to enable business focused high impact analytics solutions driven by modern data architecture platforms.

During his time as Slalom’s practice director, his business targets included data science solutions in areas such as clinical trial management and financial services customer behavior. He and his team developed modern data architecture (including cloud) solutions to support challenges in Data Warehousing, Big Data management, Data Governance and Real time data capture and scaling of  corporate data platforms. While at the Microsoft Technology Center in Cambridge and at Tripadvisor.com, he honed his skills on the Microsoft BI platform and advanced data platform architectures, including HADOOP and “Big Data” technologies. His visionary approach to the Data focuses on helping companies stay competitive through acceleration and business impact, as evidenced by work he had done creating a BI maturity model and an Analytics Reference Architecture. He is a published author and speaks at industry/technology events. Other past roles include Director of Data Platforms at BlueMetal Architects; Data Warehouse/BI/CRM Manager at TripAdvisor; Technology Architect at Microsoft; Lead Systems Engineer for MITRE; as well as several other software engineering and business intelligence related positions.

Carmen earned a Master in Systems Engineering from Boston University and a Bachelor of Computer Science from Rochester Institute of Technology.

Valeria Tivnan, M.P.H., M.Ed.

Adjunct Faculty Member, Data Science & Analytics

Ms. Tivnan is currently part of the adjunct faculty for the Data Science and Health Science programs at Merrimack College.  With over 20 years of experience, her passions are in wellness, disease prevention, and population health management.  Ms. Tivnan holds two master’s degrees in Education and Public Health and has spoken for the American Diabetes Association, the American Journal of Health Promotion and the World Research Group.  She has currently remained engaged in health promotion as a member of organizations such as HERO (Health Enhancement Research Organization) and the American College of Lifestyle Medicine.  Val has been committed to driving and delivering results-driven wellness programs, and has done so for various organizations, including one of the largest hospital chains in the United States.

As an instructor for the Population Health Analytics class for the M.S. in Healthcare Analytics program, Ms. Tivnan is inspired to motivate our younger generation of business professionals to help them find their purpose and opportunity in their professional careers.

Torrey Walker, M.Ed.

Success Coach, Data Science & Analytics

Success Coach

Torrey is our success coach for the Data Science & Analytics program and is very important to the overall student experience.  Throughout your time in working towards your degree, Torrey will help address many of the questions you may have “outside the classroom”.  In doing so, Torrey will help free more of your time to concentrate on mastering the content that is so important to your program progression.

Torrey has earned her BA in Mathematics from the College of the Holy Cross and has earned her M.Ed. in Higher Education from Merrimack College.  You will get to engage with Torrey from the time you are admitted until the time you graduate, allowing you to have a consistent point of contact as you work to achieve your goals!

Jeremiah Lowhorn

Data Scientist, Data Tapestry; Programming Mentor for R and Python, Data Science & Analytics

Programming Mentor

Jeremiah is a Data Scientist with nine years of experience in analytics. He is currently a Senior Data Scientist at Data Tapestry, formerly PYA Analytics.  His interests include computer vision, natural language processing, time series analysis, and distributed computing. Jeremiah is fluent in R, Python, VBA, SQL, and is interested in learning new programming languages.

In his leisure he spends time with his wife Brooke and son Magnus. Jeremiah holds a BS in Financial Analysis from Ball State University, a MS in Analytics from Dakota State University, and is pursuing an MSIS and PhD from Dakota State University. He assists the graduate program students by providing mentorship in R, Python, and Data Science on an as needed basis.