Dr. Andrew Banasiewicz is the Director of Data Science and Business Analytics programs at Merrimack College; he is also the founder and a principle of Erudite Analytics, a data analytical consultancy. Prior to joining Merrimack College, Dr. Banasiewicz held a full-time faculty appointment at Boston University; he also formerly served as a part-time faculty member at Providence College and Harvard University, and a visiting lecturer at Audencia Business School in France and Bandung Institute of Technology in Indonesia.
Before embarking on academic and consulting career, Dr. Banasiewicz spent over 15 years in industry in senior-level quantitative analytics positions, most recently serving as a director of data science at an insurance company, and a senior vice president of analytics at an insurance brokerage firm. His primary area of expertise is predictive risk analytics, research design, and text mining; he has extensive, hands-on data analytical experience in a wide range of industries, including energy, utilities, automotive, financial services, pharmaceuticals, consumer packaged goods, gaming and hospitality.
Dr. Banasiewicz wrote four analytics-focused books, in addition to contributing multiple methodological journal articles and industry white papers; he is also a frequent speaker at national and international professional meetings and conferences, including the bi-annual Global Risk Forum in Davos, Switzerland. He is a member of the Society of Risk Management Consultants, where he serves as the Chair of Professional Practices, the Society for Risk Analysis, and the Professional Liability Underwriting Society; he is also a Fellow of the Claims and Litigation Management Alliance, and the Australian Academy of Business Leadership.
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.
Dr. Fotios Kokkotos is an accredited professional statistician (PStat®, one of about 300 in the world) by the American Statistical Association with over 25 years of experience in statistical consulting. Dr. Kokkotos specializes in the analysis of massive and complex health care datasets using sophisticated statistical techniques. Dr. Kokkotos has a wide range of experience in many areas of statistics, including but not limited to modeling patient health outcomes, sampling theory, survey designs, statistical modeling and forecasting, statistical computing, categorical data analysis, nonparametric statistics, stochastic processes, time series and mathematical finance. Dr. Kokkotos has an extensive knowledge and research completed with secondary public health data. His current research interests are the application of statistics, data mining and statistical computing in efficiently exploring and integrating very large databases under the constraints of shared distributed memory and concurrent programming algorithms. Dr. Kokkotos has been the author and reviewer of numerous articles and poster presentations in many scientific journals and conferences. Dr. Kokkotos has been involved in many academic research collaborations in the area of health outcomes with colleagues from top universities, such as Harvard, Cornell, Tufts, Michigan, Northwestern and Boston University.
Dr. Kokkotos held the position of senior statistician at the global statistics practice of PricewaterhouseCoopers LLP, where he provided statistical support to clients from various industry sectors that included life sciences, financial services, telecommunications and consumer products. Dr. Kokkotos has also been an adjunct faculty member of statistics at the American University in Washington, D.C. Dr. Kokkotos is a long time member of the American Statistical Association and the Mathematical Association of America. Dr. Kokkotos obtained a doctorate degree in mathematical statistics from The American University.