PART-TIME | FULL-TIME | STEM
Master's in Finance
Get a firm grasp of both theory and practice by using state-of-the-art information and analysis software throughout the program.
Bentley University offers two paths for students to tailor their degree to their career goals, Finance or Financial Analytics. The traditional Finance Path can be completed in 11 to 16 months, including a summer internship, while the Financial Analytics Path comprises 10 courses focused on financial mathematics and statistical analysis and can be completed in 12 to 16 months.
Students can choose their path at any point before their second semester. Bentley's Financial Analytics Path is STEM-designated, which means that international students can apply for an additional 24 months of OPT after graduation, bringing the total to three years. Bentley also has partnerships with the GARP and CFA Institute for their designations and offers Bloomberg certification courses on their 24 on-campus Bloomberg terminals.
Highlights
The STEM-based Financial Analytics path incorporates Bentley’s three course analytics core—a distinctive feature of all our Analytics programs. This allows students interested in risk analysis, risk management, financial analysis, investment management, and financial technology to develop a distinctive skill set that meets the more than 2 million new analytics jobs expected to be created in the near future.
As with all of Bentley’s STEM-based Master of Science degrees, international students pursuing the Financial Analytics path are eligible for an extended Optional Practical Training (OPT) period. OPT is temporary employment that is directly related to an F-1 student’s major area of study and allows international students to gain up to three years of valuable work experience at top employers in the U.S. While sponsorship of international students from U.S. universities has declined in recent years, the demand for STEM OPT remains strong among Bentley’s Analytics graduates.
The Bentley MSF prepares you for a wide range of careers, no matter the industry you are interested in. See below for a partial list of employers and job titles our alumni have achieved over the past year.
Company Name | Alumni Title |
Fidelity Investments | Research Analyst |
State Street | Corporate Actions Research Analyst |
Brown Brothers Harriman | Chief Account Manager, Investor Services |
Longfellow Investment Management | Research Analyst |
National Grid | Financial Analyst |
Everquote | Financial Analyst |
Boston Scientific | Financial Analyst II |
Analog Devices | FP&A Senior Financial Analyst |
Stanley Black & Decker | Leadership Development Program, Finance |
East Boston Savings Bank | Credit Analyst |

Bentley MSF students make extensive use of the multimillion-dollar Bentley Trading Room in course work and case studies, using tools like Bloomberg, FactSet, Morningstar, Capital IQ, S&P Compustat, and ThomsonOne Analytics. You can also get involved with B.I.G., the Bentley Investment Group, a student-run organization that invests a portion of the Bentley University endowment.
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Tuition and Aid
At Bentley, we do everything possible to make your education affordable for you and to provide the kind of return on investment you expect — and deserve. With available merit and financial aid, Bentley works with qualified applicants to help find ways to pay for their education.
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Top Employers Hiring Our Graduates

Curriculum
The Masters of Science in Finance can be completed through either a 10-course finance path or financial analytics path. The STEM-designated Financial Analytics track has a mathematical and capital market focus that will appeal to students interested in risk analysis, risk management, compliance, investment, and financial technology. Depending on prior education and experience, students may be required to take up to four pre-program foundation courses.
Foundation Courses
All applicants will be evaluated for foundation waivers.
This course covers basic statistical techniques in a managerial setting, and features case studies and conceptual exercises. Statistical topics include effective use of numerical and graphical summaries, estimation and confidence intervals, hypothesis testing and regression. More advanced topics such as data mining, the Bayesian paradigm and principles of model building, may be encountered during projects.
This course examines managerial decision-making from an economic standpoint. The first half (microeconomics) explores how prices, wages and profits are determined in market economies; the advantages and disadvantages of unfettered competition; and the impact of government intervention on market outcomes. The second half (macroeconomics) investigates the factors influencing gross domestic product, interest rates, unemployment, inflation and growth; the causes of the business cycle; the role of the federal government and the Federal Reserve in stabilizing the economy; the impact of technology on productivity and growth; and the influence of international trade and finance on economic activity.
This course highlights how managers use cost, cash flow and financial reporting information in their decisions. It will introduce the student to (a) purpose of accounting and its role in making business decisions, (b) accounting principles, procedures and judgments underlying corporate financial statements, (c) use, interpretation and limitations of financial statements, (d) use and interpretation of cost accounting data in managerial decision-making, and (e) approaches to identify problems, analyze their financial and managerial implications, and evaluate alternative solutions.
The course presents differential and integral calculus in a single variable, with connections to further study in continuous probability, multivariate calculus and differential equations. Specific emphasis is placed on tools relevant to later study of computational finance. Topics include limits, continuity, differentiation of single-variable and multivariate functions, implicit differentiation, optimization, integration by substitution and by parts, numerical integration, and introductions to ordinary differential equations, continuous probability, and Taylor series.
Core Courses: Finance Path
This course provides fundamental knowledge in key areas of investments. In particular, the course will focus on portfolio theory, asset pricing, equity valuation, fixed income valuation and risk, and option pricing and strategies.
The course extends the basic understanding of financial concepts and tools by emphasizing the modern fundamentals of the theory of finance. It develops the ability to apply financial analysis, planning and valuation techniques to solving financial problems. The course covers issues related to how managers manage the assets in place, identify and evaluate future investment opportunities, and analyze sources and costs of capital necessary to fund these projects. Topics are presented in an environment that includes strategic, global and technological issues where appropriate and relevant.
Financial Modeling is focused on applying sophisticated Excel techniques to the most common modeling problems in finance. The skill set is expanded to include advanced features of Excel including TVM and statistical functions, array manipulation, text and date usage, regression, conditionals, Boolean operators, data tables and random number generation. Subsequently the course will cover macro recording as well as custom subroutine and function construction in the Visual Basic for Applications (VBA) development environment. All techniques learned will be applied to the most common financial modeling problems of the day including financial statement forecasting, present value, cost of capital, and valuation.
This course deals with the international aspects of corporate finance and investing. Areas covered include foreign exchange with emphasis on exchange rate determination, exchange risk, hedging and interest arbitrage, international money and capital markets and international financing, multinational capital budgeting, cost of capital and international portfolio management.
This course provides students with an in-depth coverage of simple and multiple linear regression methods and, as time permits, an introduction to the analysis of time series data. Simple and multiple linear regression techniques are covered, including the use of transformations such as squares and logarithms, the modeling of interactions, and how to handle problems resulting from heteroscedasticy and multicollinearity. Issues surrounding outlying and influential observations are also covered. The art and science of model building are demonstrated with the help of cases. Autocorrelation is then considered, and an introduction to the ARIMA modeling of times series is provided. This course makes use of statistical packages such as SAS, JMP, R or SPSS.
Elective Courses: Finance Path
Finance Elective (4): Any four graduate Finance electives.
Outside Elective (1): The remaining fifth elective may be in FI, or any non-FI elective at the 600 level or above
Core Courses: Financial Analytics Path
This course teaches foundational data management,retrieval, and manipulation skills with an emphasis on enabling the students to form a strong foundation for analytical processes. It builds a foundation for understanding various domains of practice with conceptual data modeling and demonstrates how the same conceptual needs can be served with different data management technologies. The course covers relational technologies for both operational databases and data warehouses and non-relational data management infrastructures for analytics. The course will help the students develop strong skills in the use of the SQL language for database definition and data manipulation.
This course provides fundamental knowledge in key areas of investments. In particular, the course will focus on portfolio theory, asset pricing, equity valuation, fixed income valuation and risk, and option pricing and strategies.
The course extends the basic understanding of financial concepts and tools by emphasizing the modern fundamentals of the theory of finance. It develops the ability to apply financial analysis, planning and valuation techniques to solving financial problems. The course covers issues related to how managers manage the assets in place, identify and evaluate future investment opportunities, and analyze sources and costs of capital necessary to fund these projects. Topics are presented in an environment that includes strategic, global and technological issues where appropriate and relevant.
Financial Modeling is focused on applying sophisticated Excel techniques to the most common modeling problems in finance. The skill set is expanded to include advanced features of Excel including TVM and statistical functions, array manipulation, text and date usage, regression, conditionals, Boolean operators, data tables and random number generation. Subsequently the course will cover macro recording as well as custom subroutine and function construction in the Visual Basic for Applications (VBA) development environment. All techniques learned will be applied to the most common financial modeling problems of the day including financial statement forecasting, present value, cost of capital, and valuation.
This course provides materials and projects that will allow students to develop a detailed understanding of the design, mechanics and pricing of derivative securities in risk management. The concept of the law of one price will be stressed and includes the application of the tools and inputs (quantitative techniques as developed in ST 625) necessary to value derivative securities. The mathematical requirements of the course are primarily algebraic, but the student will also need to rely on statistical methods and some calculus. Please note that this is not a survey course. It is an intensive introduction to derivative securities pricing and market mechanics.
The course covers the application of advanced mathematical methods to solve complex problems in Finance. Mathematical topics will include computational methods, simulation methods, numerical methods and stochastic processes. The course presumes an advanced understanding of financial markets and instruments and will use software such as MATLAB extensively for a series of application projects.
The course will provide a business-focused perspective on analytics in organizations, with emphasis on business fundamentals for analytics professionals (including how businesses are structured, functional areas, core business processes and associated performance metrics, and types of business decisions), the value of analytics in organizations (including organizational-level perspectives on value, managing with analytics, and constraints and consequences of analytics processes such as information security, privacy and ethics), and the practice of analytics (understanding and framing ill-defined business problems in various functional business areas, exploring and visualizing problem-related data, identifying actionable insights, and communicating the results at different organizational levels). The course will feature hands-on exercises with real-world data and analytics applications.
This course provides students with an in-depth coverage of simple and multiple linear regression methods and, as time permits, an introduction to the analysis of time series data. Simple and multiple linear regression techniques are covered, including the use of transformations such as squares and logarithms, the modeling of interactions, and how to handle problems resulting from heteroscedasticy and multicollinearity. Issues surrounding outlying and influential observations are also covered. The art and science of model building are demonstrated with the help of cases. Autocorrelation is then considered, and an introduction to the ARIMA modeling of times series is provided. This course makes use of statistical packages such as SAS, JMP, R or SPSS.
Elective Courses: Financial Analytics Path
Finance Elective (1): Any graduate Finance elective.
Analytics Elective (1): Any graduate elective in Computer Science, Mathematics, or Statistics.
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Application Deadlines

Meet Your Program Director
Florin is a lecturer and the program director of the MS in Finance at Bentley University. He received an MBA and a PhD in Engineering, both from Massachusetts Institute of Technology (MIT). Florin has a balanced background of quantitative and fundamental analysis skills as well as hands-on experience in the markets. He was an equity analyst at Blackstone Asia Advisors responsible for equity research on Technology, Telecom and Alternative Energy sectors in Asia. Before joining Blackstone, he developed quantitative trading strategies for Castor Pollux Securities, a start-up hedge fund in Boston. Florin Morosan also held equity research positions at Sanford Bernstein, Citigroup and Robertson Stephens and worked for McKinsey & Co. as a management consultant. His teaching interests are derivatives, investments and international finance.
Contact Florin to schedule a time to discuss your background and career goals and how these align with Bentley's MSF program.