“Annual demand for the fast growing new roles of data scientist, data developers, and data engineer will reach nearly 700,000 openings by 2020.”*
Meet our current students: M.S in Business Analytics Student Directory.
To learn more about our M.S. in Business Analytics class profile, click here.
To meet some of our M.S. in Business Analytics alumni and alumnae, click here.
Businesses that know how to analyze and apply data (big or small) outperform competitors by up to 20 percent. Why, then, do so few companies draw powerful insights from data? The answer is simple – a lack of in-house talent. Lally’s Master’s of Science in Business Analytics will prepare you to meet the biggest demand of 21st century business.
Fei Xie ’16 M.S. in Business Analytics:
Our curriculum follows foundational business concepts with data management and statistical modeling, which you will customize with electives that include natural language processing, machine learning, marketing, and supply-chain management. You will learn to think critically about data. You will have access to diverse data sets, powerful computing and visualization resources, and real-world applications possible only at Rensselaer. We offer a small class size, dedicated faculty, and hands-on experience through class projects, and a capstone course with industry partners. The experience at Lally also includes mentoring from a highly engaged advisory board of executives in the business analytics profession.
Our students come from the U.S., China, and India, as well as other countries. Students’ backgrounds range from business, to sciences, to engineering. Eight-six percent of our 2016-2017 graduates had jobs within three months of graduation, with an average salary of $73,856. Companies that have hired our graduates include: IBM, Research Now, Dentsu Aegis Network, Cisco Systems, The Comcast Corporation, Facts & Measures, Accenture, Dish Network, WalMart, QueBIT, LL Bean, and CDPHP.
Graduates are prepared to take first steps toward a transformative career as a data scientist, quantitative consultant, market and consumer analyst or any of the large and rapidly growing data driven positions within industry.