Indiana University Bloomington

What you'll study

This programme combines mathematical modelling, statistical inference and computing to solve real-world management problems. Core topics typically include optimisation and linear programming, stochastic models and queuing theory, simulation, multivariate statistics and econometrics, predictive analytics and machine learning, database design and SQL, and programming for analytics (commonly Python and R). Elective options frequently cover supply chain analytics, revenue management, risk analysis, time-series forecasting, causal inference, and advanced topics in operations research such as integer programming and network flows.

Coursework is designed to balance theory and application. Students usually complete a sequence of foundational quantitative modules before moving to applied courses and a culminating experience, which may be a capstone project with an external partner, an applied practicum, or a supervised research/thesis option. Practical components emphasise data management, model implementation, and communicating results to managerial audiences.

Entry requirements

Applicants should hold a recognised bachelor’s degree or equivalent from an accredited institution. A strong quantitative background is expected; typical preparation includes undergraduate coursework in calculus, linear algebra, probability and statistics. Applicants with degrees in mathematics, statistics, engineering, economics, computer science or business are well placed for admission.

Typical application materials include academic transcripts, a current CV or résumé, a personal statement describing quantitative preparation and career goals, and at least two academic or professional references. Many programmes consider GRE or GMAT scores where provided, though requirements may vary; international applicants must demonstrate English proficiency through recognised tests unless otherwise exempt. Relevant work or research experience in analytics, programming, or quantitative modelling can strengthen an application.

Career prospects

Graduates enter a wide range of analytical and management roles. Common job titles include data scientist, business or management consultant, operations analyst, supply chain analyst, revenue or pricing analyst, risk analyst, and quantitative model developer. Employers span sectors such as technology, finance, consulting, healthcare, manufacturing, retail and government agencies.

The programme also prepares students for doctoral study in operations research, management science or related fields for those interested in academic or research careers. Emphasis on applied projects and internships helps graduates build portfolios of practical work that employers seek.

Why study at Indiana University Bloomington

Indiana University Bloomington’s Kelley School of Business is known for integrating rigorous quantitative training with applied business perspectives. Students benefit from access to faculty who publish in operations research, analytics and decision sciences, as well as from interdisciplinary collaborations across economics, informatics and engineering.

Kelley provides experiential learning opportunities such as industry-sponsored capstones, practicum placements and internship pipelines with corporate and public-sector partners. Career services and an active alumni network support recruiting and professional development. The Bloomington campus offers computing and analytics resources, student organisations focused on data science and operations, and a collaborative environment for developing both technical skills and business judgement.