Doane University

What you'll study

This programme combines graduate-level training in statistical modelling, optimisation and computational methods with applied management courses. Core study areas typically include probability and inferential statistics for decisions, multivariate analysis, predictive analytics and machine learning, optimisation and operations research (linear and nonlinear programming, network flows), stochastic modelling and simulation, decision analysis and risk management, and database design and data management.

Students learn practical tools and languages commonly used in industry, such as Python or R for data science, optimisation solvers, and SQL for data handling. The curriculum emphasises applied projects: courses often integrate case studies from supply chain, healthcare, finance and public policy to show how quantitative methods support real organisational choices.

Programme structure generally includes a combination of core modules, electives that allow specialisation (for example in supply chain analytics, healthcare analytics, or financial risk), and a substantial culminating experience—either a capstone practicum with an external partner or a thesis-like research project supervised by faculty.

Entry requirements

Applicants are normally expected to hold a recognised bachelor’s degree. A degree in business, economics, mathematics, statistics, engineering, computer science or a related field is advantageous; candidates from other disciplines who can demonstrate quantitative aptitude are also considered.

• Official academic transcripts from prior institutions.
• A resume or curriculum vitae outlining relevant academic and professional experience.
• A personal statement describing goals, quantitative background and reasons for pursuing the programme.
• Letters of recommendation (usually one to three) from academic or professional referees.
• Evidence of competency in mathematics and statistics — for some applicants this may be demonstrated by prior coursework (calculus, linear algebra, introductory statistics) or relevant work experience.
• Where English is not the applicant’s first language, satisfactory English language test scores or other proof of proficiency may be required.

Standardised test requirements (such as GRE/GMAT) and professional experience expectations vary; prospective students should check with admissions for possible waivers or alternative evidence of preparedness.

Career prospects

Graduates move into roles that require quantitative decision-making and data analysis. Common career paths include operations research analyst, data scientist or data analyst, supply chain analyst, business analyst, management consultant, risk analyst, and roles in pricing, forecasting or revenue management. Employers span the private and public sectors: manufacturing and logistics companies, healthcare providers, financial services, technology firms, consulting practices and government agencies.

Beyond immediate employment, the degree also provides a foundation for doctoral study in fields such as operations research, applied statistics or management science for those interested in research or academic careers.

Why study at Doane University

Doane offers a learner-focused environment with smaller class sizes that allow close interaction with faculty and hands-on supervision for project work. The university emphasises applied learning, connecting quantitative methods to organisational problems through capstones, practicum partnerships and internship opportunities with regional and national organisations.

Faculty teaching in the programme typically combine academic qualifications with applied experience in analytics, operations and business domains, bringing real-world perspective into the classroom. Students benefit from access to computing resources and software used by industry, plus career services that support placement, networking and professional development. Flexible delivery options accommodate working professionals seeking to study part-time or combine online and on-campus study.