Online MS in Financial Management—AI Applications

At a Glance

Completion Time

8–16

Months

Credits Required

Tuition

$25,452–$27,204

Part-Time*

*Based on 2025–2026 Boston University tuition and fees. Merit scholarship may reduce cost.

Unlock Career Success with AI-Driven Financial Modeling and Advanced Analytics

The online MS in Financial Management concentration in AI Applications is designed for professionals pursuing roles in FinTech, algorithmic trading, quantitative analysis, and risk management. Gain advanced skills in artificial intelligence-powered financial modeling, machine learning, and data analytics tailored for the finance industry.

Through a rigorous and practical curriculum, you will master AI methodologies such as natural language processing, predictive analytics, and deep learning, applying these tools to asset allocation, algorithmic trading strategies, fraud detection, and risk assessment. The Financial Management master’s concentration in AI Applications enables you to transform traditional finance approaches by leveraging data-driven insights and innovative AI solutions to drive smarter investment and decision-making processes.

As a graduate of BU MET’s MS in Financial Management concentration in AI Applications, you will be prepared to excel in dynamic roles that demand expertise in technology-enhanced finance, including investment analysis, market strategy, and operational efficiency. The program also incorporates a significant portion of the CFA® Program Candidate Body of Knowledge™ (CBOK) and the Standards of Practice Handbook, preparing you for the Chartered Financial Analyst® exams, with scholarships for the exams available for enrolled students.

Metropolitan College is a participant in the CFA Institute University Affiliation Program. This membership acknowledges that our MSFM degree and concentration curricula embed a significant portion of the CFA^® Program Candidate Body of Knowledge™ (CBOK) and cover the Standards of Practice Handbook, offering excellent preparation for the internationally recognized Chartered Financial Analyst^® (CFA) Program exams.

The MS in Financial Management, AI Applications concentration is also available on campus in Boston. Learn more.

Curriculum

A total of 32 units is required.

Students must complete the degree core courses and AI Applications concentration requirements:

Core Courses

(Four courses/16 units)

MET AD 504 Financial and Managerial Accounting

4 credits.

Introduction to the concepts, methods, and problems of financial and managerial accounting. Includes data accumulation, accounting principles, financial statement analysis, measurement and disclosure issues, cost analysis, budgeting and control, production costs, and standard costs.

Section A1, SPRG 2026 Jan 20th to Apr 30th
Instructor	Type	Days	Times	Location
Sam-Kwachie	Independent	M	02:30:00 PM–05:15:00 PM	CAS 237

Section O1, SPRG 2026 Jan 13th to Mar 2nd
Instructor	Type	Days	Times	Location
Chee	Independent	ARR	12:00:00 AM–12:00:00 AM

MET AD 522 Corporate Finance

4 credits.

Prerequisite: MET AD 504. Emphasizes issues of accounting, finance, and economics that are important in most management contexts. Stresses understanding of financial statements, corporate planning and control, cost and benefit evaluation, cash flow analysis, and capital budgeting.

Section A1, SPRG 2026 Jan 20th to Apr 30th
Instructor	Type	Days	Times	Location
Ge	Independent	R	06:00:00 PM–08:45:00 PM	EPC 206

Section O2, SPRG 2026 Mar 10th to Apr 27th
Instructor	Type	Days	Times	Location
Ge	Independent	ARR	12:00:00 AM–12:00:00 AM

MET AD 678 Financial Regulation and Ethics

4 credits. Fall and Spring

Financial Regulation and Ethics is a course designed to thoroughly review the important topics of financial regulations, policies, and ethics. The course will explore an overview of the financial systems, their history, problems, and issues for the purpose of understanding the enactment of regulations as a method to protect the financial systems and investors. Also, regulators and their authority will be identified, both domestically and internationally. Ethics, an extremely important aspect of finance will be discussed and explored. Ethics is a difficult topic to define and can be impacted by social norms. During the ethics portion of the course, students will study where ethics have failed and caused major issues for the financial marketplace and individual companies.

Section A1, SPRG 2026 Jan 20th to Apr 30th
Instructor	Type	Days	Times	Location
Shimer	Independent	T	12:30:00 PM–03:15:00 PM	MCS B29

Section O2, SPRG 2026 Mar 10th to Apr 27th
Instructor	Type	Days	Times	Location
Vodenska	Independent	ARR	12:00:00 AM–12:00:00 AM

MET AD 685 Quantitative Methods for Finance

4 credits. Fall and Spring

Finance is a highly competitive and dynamic industry that demands quantitative oriented professionals. This course will equip students with the empirical techniques which are used in the analysis of financial markets with a strong focus on financial applications using actual data. The goal of this course is to provide students with a number of econometric techniques which are used in the analysis of financial markets based on asset pricing and corporate finance models. In particular, the emphasis will be on classical linear regression models, time series analysis, and limited dependent variable models applied to the following topics: predictability of asset returns; event study analysis; econometric tests of the CAPM and multifactor models; volatility modelling, etc.

Section A1, SPRG 2026 Jan 20th to Apr 30th
Instructor	Type	Days	Times	Location
Julio	Independent	M	06:00:00 PM–08:45:00 PM	SHA 202

Section A2, SPRG 2026 Jan 20th to Apr 30th
Instructor	Type	Days	Times	Location
Julio	Independent	W	02:30:00 PM–05:15:00 PM	MCS B37

Section O1, SPRG 2026 Jan 13th to Mar 2nd
Instructor	Type	Days	Times	Location
Julio	Independent	ARR	12:00:00 AM–12:00:00 AM

Concentration Requirements

(Four courses/16 units)

MET AD 561 Financial Analytics

4 credits. Fall and Spring

This course presents financial algorithms used in applications of computer science in financial decision analysis, risk management, data mining and market analysis, and other modern business processes. The course covers theoretical background on probabilistic methods used for financial decision making and their application in number of fields such as financial modeling, venture capital decision making, operational risk measurement and investment science. Number of financial applications and algorithms are being presented for portfolio risk analysis, modeling real options, venture capital decision making, etc. The course concludes with algorithms for financial risk assessment and presents the security concepts and challenges of financial information systems.

Section A1, SPRG 2026 Jan 20th to Apr 30th
Instructor	Type	Days	Times	Location
Page	Independent	T	06:00:00 PM–08:45:00 PM	STH B19

MET AD 698 Applied Generative AI for Business Analytics

4 credits.

Prerequisite: MET AD571 Generative AI is transforming industries by automating tasks, generating content, and assisting in decision-making. This hands-on course explores how business professionals, analysts, and managers can apply Generative AI to solve real-world business challenges. The course emphasizes practical AI applications, covering topics like prompt engineering, AI-driven workflow automation, AI-powered data analytics, and responsible AI practices. Students will gain experience using Jupyter Notebooks, VS Code, SQL, and GitHub to integrate AI into their workflows.

Section A1, SPRG 2026 Jan 20th to Apr 30th
Instructor	Type	Days	Times	Location
Padalkar	Independent	M	06:00:00 PM–08:45:00 PM	CDS 364

MET CS 664 Artificial Intelligence

4 credits.

Prerequisites: MET CS 248 and MET CS 342. - Study of the ideas and techniques that enable computers to behave intelligently. Search, constraint propagations, and reasoning. Knowledge representation, natural language, learning, question answering, inference, visual perception, and/or problem solving. Laboratory course.

Section A1, SPRG 2026 Jan 20th to Apr 30th
Instructor	Type	Days	Times	Location
Kalathur	Independent	M	06:00:00 PM–08:45:00 PM	MET 101

Section O1, SPRG 2026 Jan 13th to Mar 2nd
Instructor	Type	Days	Times	Location
Mansur	Independent	ARR	12:00:00 AM–12:00:00 AM

And one general elective chosen with an academic advisor:

Elective Courses

MET AD 528 Blockchain Finance

4 credits. Fall and Spring

Cryptocurrencies and the underlying distributed ledger technology (blockchain), have exploded into public consciousness over the last few years, with many industry practitioners arguing that the blockchain technology has the potential to disrupt business and financial services in the way the Internet disrupted off-line commerce. This course covers digital currencies, blockchains, and related topics in the FinTech area using the analytical tools provided by economics, investments and corporate finance.

Section A1, SPRG 2026 Jan 20th to Apr 30th
Instructor	Type	Days	Times	Location
Julio	Independent	T	06:00:00 PM–08:45:00 PM	CAS B06B

MET AD 580 Environmental, Social, and Governance (ESG) Investments

4 credits. Fall and Spring

Prerequisites: MET AD 717 or consent of instructor.- A comprehensive investments course introducing important aspects of investing, including environmental, social, and governance issues, and their role in corporate risk management, financial markets, and investments, presented from the viewpoint of market participants and corporate leadership. The course incorporates the mechanics of investing sustainably, with long-term planning on a micro and macro level. Topics will include an introduction and understanding of the ESG market, defining the environmental, social, and governance factors important for investment decision-making, and the importance of corporate engagement and stewardship. The course will also cover ESG analysis, valuation, and integration in portfolio management.

Section O1, SPRG 2026 Jan 13th to Mar 2nd
Instructor	Type	Days	Times	Location
Vodenska	Independent	ARR	12:00:00 AM–12:00:00 AM

MET AD 599 Python and SQL for Business Analytics

4 credits. Fall and Spring

Prerequisites: AD100 - Python is a modern, high-level programming language. One of the most popular programming languages, its use has steadily increased across a large number of industries. This course introduces students to the Python environment and teaches a solid foundation in the basic syntax and structure. Structured Query Language (SQL) is the most common language globally for interacting with relational databases. Employers have indicated that knowledge of SQL is one of the most important skills for new graduates entering the workforce. Even with advances in database technologies and languages for handling heterogeneous data types, SQL remains the core skill for interacting with data. This course introduces both languages to equip students pursuing an analytics education with the skills necessary to succeed in the analytics and data visualization field. The outcome of this course will be a focused survey of Python and SQL topics designed to equip analytics professionals rather than a deep focus on technical programming topics.

Section A1, SPRG 2026 Jan 20th to Apr 30th
Instructor	Type	Days	Times	Location
Valath Bhuan Das	Independent	M	06:00:00 PM–08:45:00 PM	CAS 204A

Section A2, SPRG 2026 Jan 20th to Apr 30th
Instructor	Type	Days	Times	Location
Yu	Independent	R	06:00:00 PM–08:45:00 PM	CAS 208

Section O1, SPRG 2026 Jan 13th to Mar 2nd
Instructor	Type	Days	Times	Location
Yu	Independent	ARR	12:00:00 AM–12:00:00 AM

MET AD 616 Enterprise Risk Analytics

4 credits. Fall and Spring

Prerequisite: MET AD 571. - The course offers an overview of the key current and emerging enterprise risk analytical approaches used by corporations and governmental institutions and is focused on understanding and implementing the enterprise risk management framework on how to leverage the opportunities around a firm to increase firm value. The major risk categories of the enterprise risk management such as financial risk, strategic risk, and operational risk will be discussed and risk analytics approaches for each of these risks will be covered. Students will learn how to use interlinked data inputs, analytics models, business statistics, optimization techniques, simulation, and decision-support tools. An integrated enterprise risk analytics approach will be demonstrated with examples from different functional areas of the enterprise. Python, R, SQL, and Power BI software are used in this course.

Section A1, SPRG 2026 Jan 20th to Apr 30th
Instructor	Type	Days	Times	Location
Yu	Independent	M	06:00:00 PM–08:45:00 PM	CAS 228

Section A2, SPRG 2026 Jan 20th to Apr 30th
Instructor	Type	Days	Times	Location
Parzen	Independent	T	12:30:00 PM–03:15:00 PM	COM 217

MET AD 633 Social Innovation and Entrepreneurship

4 credits.

This course equips students with the skills and knowledge to drive social change through innovative entrepreneurial ventures. It explores the fundamental frameworks and theories of social innovation while teaching students how to identify and tackle social needs effectively. Participants will learn to create sustainable business models that are both economically viable and scalable, ensuring a long-term impact. The curriculum includes strategies for scaling social ventures, measuring their impact, and engaging with diverse stakeholders to promote collaborative change. Students will examine various funding options available to social entrepreneurs, such as impact investing and crowdfunding, and discover how to influence policy and advocate for supportive environments.

Section A1, SPRG 2026 Jan 20th to Apr 30th
Instructor	Type	Days	Times	Location
Goncalves	Independent	M	06:00:00 PM–08:45:00 PM	CAS 116

MET AD 654 Marketing Analytics

4 credits. Fall and Spring

Prereq: METAD 571. Become familiar with the foundations of modern marketing analytics and develop your ability to select, apply, and interpret readily available data on customer purchase behavior, new customer acquisition, current customer retention, and marketing mix optimization. This course explores approaches and techniques to support the managerial decision-making process and skills in using state-of-the-art statistical and analytics tools. Students will have an opportunity to gain a basic understanding of how transaction and descriptive data are used to construct customer segmentation schemas, build and calibrate predictive models, and quantify the incremental impact of specific marketing actions. Python, R, SQL, and Power BI software are used in this course.

Section A1, SPRG 2026 Jan 20th to Apr 30th
Instructor	Type	Days	Times	Location
Page	Independent	M	02:30:00 PM–05:15:00 PM	MET 101

Section A2, SPRG 2026 Jan 20th to Apr 30th
Instructor	Type	Days	Times	Location
Page	Independent	M	06:00:00 PM–08:45:00 PM	FLR 121

Section O1, SPRG 2026 Jan 13th to Mar 2nd
Instructor	Type	Days	Times	Location
Page	Independent	ARR	12:00:00 AM–12:00:00 AM

MET AD 688 Big Data and Cloud Analytics for Business

4 credits. Fall and Spring

Prerequisite: MET AD571 Work with large, complex datasets beyond traditional desktop analytics using Apache Spark (PySpark), DuckDB, Polars, SQL-based data warehousing, and AWS cloud services. You will explore vector databases, feature engineering pipelines, and scalable machine-learning workflows using Spark MLlib. Key topics include parallel processing, management of massive data stores, cloud data architectures, web scraping, API-based data collection, text and web mining, and batch and streaming analytics. You will complete end-to-end analytics workflows, from data ingestion and cleaning to modeling, evaluation, and communication, using Python (PySpark), SQL, Git, and GitHub in a cloud-ready AWS environment. By the end of the course, you will be able to design scalable analytics pipelines, manage cloud data environments, and apply distributed machine learning to real-world datasets. The course culminates in a term project implementing a complete big data and cloud analytics workflow.

Section A1, SPRG 2026 Jan 20th to Apr 30th
Instructor	Type	Days	Times	Location
Valath Bhuan Das	Independent	T	06:00:00 PM–08:45:00 PM	CAS 324

Section A2, SPRG 2026 Jan 20th to Apr 30th
Instructor	Type	Days	Times	Location
Padalkar	Independent	R	12:30:00 PM–03:15:00 PM	SOC B63

Section O2, SPRG 2026 Mar 10th to Apr 27th
Instructor	Type	Days	Times	Location
Padalkar	Independent	ARR	12:00:00 AM–12:00:00 AM

MET AD 699 Data Mining for Business Analytics

4 credits. Fall and Spring

Prerequisites: AD571 Enterprises, organizations, and individuals are creating, collecting, and using a massive amount of structured and unstructured data with the goal of converting the information into knowledge, improving the quality and the efficiency of their decision-making process, and better positioning themselves in the highly competitive marketplace. Data mining is the process of finding, extracting, visualizing, and reporting useful information and insights from both small and large datasets with the help of sophisticated data analysis methods. It is part of business analytics, which refers to the process of leveraging different forms of analytical techniques to achieve desired business outcomes through requiring business relevancy, actionable insight, performance management, and value management. The students in this course will study the fundamental principles and techniques of data mining. They will learn how to apply advanced models and software applications for data mining. Finally, students will learn how to examine the overall business process of an organization or a project with the goal of understanding (i) the business context where hidden internal and external value is to be identified and captured, and (ii) exactly what the selected data mining method does. Python, R, SQL, and Power BI software are used in this course.

Section A1, SPRG 2026 Jan 20th to Apr 30th
Instructor	Type	Days	Times	Location
Ritt	Independent	M	06:00:00 PM–08:45:00 PM	STH B20

Section A2, SPRG 2026 Jan 20th to Apr 30th
Instructor	Type	Days	Times	Location
Athaide	Independent	T	12:30:00 PM–03:15:00 PM	PSY B53

Section O2, SPRG 2026 Mar 10th to Apr 27th
Instructor	Type	Days	Times	Location
Athaide	Independent	ARR	12:00:00 AM–12:00:00 AM

MET AD 709 Case Studies in Current Corporate Financial Topics

4 credits. Fall and Spring

Prerequisites: MET AD 522. Utilizes analytical methods for financial forecasting, cost of capital calculation, rate of return analysis, use of derivatives instruments, business growth management, discounted cash flow analysis, corporate valuation, mergers and acquisitions, and evaluation of bankruptcy proceedings.

Section A1, SPRG 2026 Jan 20th to Apr 30th
Instructor	Type	Days	Times	Location
Zafiropoulos	Independent	M	06:00:00 PM–08:45:00 PM	HAR 302

Section O2, SPRG 2026 Mar 10th to Apr 27th
Instructor	Type	Days	Times	Location
Barskaya	Independent	ARR	12:00:00 AM–12:00:00 AM

MET AD 713 Derivative Securities and Markets

4 credits. Fall and Spring

Provides an overview of operation, mechanics, and structure of the derivative markets and covers in-depth quantitative valuation of derivative instruments, such as options, futures, and swaps. The course involves risk analysis including risk arbitrage, and risk management. Emphasizes the theory and practice of derivatives-based trading strategies including hedging opportunities for risk mitigation.

Section A1, SPRG 2026 Jan 20th to Apr 30th
Instructor	Type	Days	Times	Location
Holmes	Independent	M	06:00:00 PM–08:45:00 PM	CAS 208

Section A2, SPRG 2026 Jan 20th to Apr 30th
Instructor	Type	Days	Times	Location
Athaide	Independent	W	02:30:00 PM–05:15:00 PM	KCB 106

Section O2, SPRG 2026 Mar 10th to Apr 27th
Instructor	Type	Days	Times	Location
Holmes	Independent	ARR	12:00:00 AM–12:00:00 AM

MET AD 719 Fixed Income Analysis

4 credits. Fall and Spring

Prerequisite: MET AD 522. Covers the nature and analysis of fixed income securities and provides an in-depth examination of some of the particular features of some major classes of fixed income instruments, valuation, sensitivity to risks, and management of fixed income portfolios.

Section A1, SPRG 2026 Jan 20th to Apr 30th
Instructor	Type	Days	Times	Location
Gil Vasquez	Independent	W	06:00:00 PM–08:45:00 PM	STH B20

Section O2, SPRG 2026 Mar 10th to Apr 27th
Instructor	Type	Days	Times	Location
Chee	Independent	ARR	12:00:00 AM–12:00:00 AM

MET AD 799 Deep Learning for Business Analytics

4 credits. Fall and Spring

Prerequisites: MET AD 599 and MET AD 571. - This course focuses on applying deep learning techniques to solve practical problems in business analytics. Students will explore foundational concepts of deep learning, including MLPs (Multi-Layer Perceptrons), Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and advanced architectures like Generative Adversarial Networks (GANs), Graph Neural Networks (GNNs), and Transformers. Through lectures, hands-on projects, and real-world datasets, students will develop the skills to design, train, and optimize deep learning models to extract insights and drive decision-making in business contexts.

Section A1, SPRG 2026 Jan 20th to Apr 30th
Instructor	Type	Days	Times	Location
Yu	Independent	T	06:00:00 PM–08:45:00 PM	CDS 263

MET CS 521 Information Structures with Python

4 credits. Fall and Spring

Creativity/Innovation
Critical Thinking
Quantitative Reasoning II

This course covers the concepts of the object-oriented approach to software design and development using Python. It includes a detailed discussion of programming concepts starting with the fundamentals of data types, control structures methods, classes, arrays and strings, and proceeding to advanced topics such as inheritance and polymorphism, creating user interfaces, exceptions and streams. Upon completion of this course students will be able to apply software engineering principles to design and implement Python applications that can be used in with analytics and big data. Effective Fall 2021, this course fulfills a single unit in each of the following BU Hub areas: Quantitative Reasoning II, Creativity/Innovation, Critical Thinking. Prerequisite: Programming experience in any language. Or Instructor's consent.

Section A1, SPRG 2026 Jan 20th to Apr 30th
Instructor	Type	Days	Times	Location
Mohan	Independent	T	06:00:00 PM–08:45:00 PM	MET 122

Section O1, SPRG 2026 Jan 13th to Mar 2nd
Instructor	Type	Days	Times	Location
Zhang	Independent	ARR	12:00:00 AM–12:00:00 AM

Section O2, SPRG 2026 Mar 10th to Apr 27th
Instructor	Type	Days	Times	Location
Trajanov	Independent	ARR	12:00:00 AM–12:00:00 AM

MET UA 549 Planning Sustainable and Climate Adapted Urban Futures

4 credits. Fall

Exploration of principles and practices essential for planning cities that are both sustainable and resilient to climate change. Strategies to create environmentally responsible, economically viable, and socially equitable urban futures will be examined. Key topics include climate adaptation and mitigation, green infrastructure, urban resilience, sustainable transportation, and energy-efficient urban design. Through case studies, policy analysis, and hands-on projects, students will develop the skills to design and implement innovative solutions that address the impacts of climate change while promoting sustainable urban development.

Section A1, SPRG 2026 Jan 20th to Apr 30th
Instructor	Type	Days	Times	Location
Autler	Independent	T	06:00:00 PM–08:45:00 PM	EPC 208

MET UA 617 Actionable Sustainability

4 credits. Fall and Spring

Sustainability generally refers to the ability of "systems" to be maintained such that they remain viable over long periods of time. As much as achieving the perfect sustainable equilibrium may be the ideal, it is important to recognize that there will be competing and conflicting interests, especially within complex hierarchical social, economic and ecological systems, particularly in light of ongoing climatic change. This field intensive course draws on the practices and theories of sustainability and climate change to understand what sustainability can mean in different contexts, and, more important, how nuanced, sustainable solutions can be achieved under varying conditions and in different systems. With an emphasis on the urban environment, the course will consist of projects in which students will identify, analyze, and develop practical proposals to real world issues. This course is intended for a wider audience from a range of disciplines.

Master’s Thesis Option

Dates & Deadlines

View BU MET’s academic calendar for online programs, including important dates and deadlines.

Application Requirements

Learn about application requirements for BU MET graduate degree and certificate programs.

A businesswoman interacting with an illustration of financial data

How You Benefit from a
Boston University Education

A BU credential can help lay the foundation for career advancement and personal success.

Benefit from an average 24:1 student-to-instructor ratio.
Work closely with highly qualified faculty who draw from active research and substantial professional achievements in areas such as international finance, financial analysis, portfolio management, systemic risk analysis, investment analysis, mergers and acquisitions, economics, financial markets and institutions, and more.
Focus on practical, hands-on lessons that ensure you are immersed in all aspects of financial management and related research—education you can apply on the job.
Expand upon classic theory taught in traditional MBA courses, gaining the insights, critical thinking, and analytical skills needed to solve problems in today’s changing financial landscape.
As part of the Chartered Financial Analyst (CFA) Institute University Affiliation Program, MET’s MS in Financial Management curriculum embeds a significant portion of the CFA® Program Candidate Body of Knowledge™ (CBOK) and covers the Standards of Practice Handbook, offering excellent preparation for the internationally recognized CFA® Program exams. In addition, scholarships for the CFA Program exam are available to enrolled students.
Learn from the best—since 2014, BU MET’s part-time master’s programs in business and management have been ranked among the top in the nation by U.S. News & World Report.

All graduate students are automatically considered for merit scholarships during the application process and nominated based on eligibility. Learn more.

Rankings & Accreditations

U.S. News & World Report - Best Online Programs - Grad Business - 2026

#12 Best Online Master’s in Business Programs (Excluding MBA)

MET’s online master’s degrees in management are ranked #12 in the nation by U.S. News & World Report.

Accredited member of AACSB International

The Association to Advance Collegiate Schools of Business (through BU’s Questrom School of Business)

MET’s Master’s in Financial Management is part of the CFA Institute University Affiliation Program.

Graduate with Financial Management Expertise

Students who complete the Financial Management master’s degree concentration in Artificial Intelligence Applications will be able to demonstrate:

Proficiency in designing, implementing, and managing AI algorithms and machine learning models to optimize financial portfolios and enhance risk-return profiles.
The ability to apply statistical and computational modeling techniques to analyze large, complex financial datasets, extracting actionable insights for both equity and fixed income markets.
Mastery of predictive analytics and forecasting tools to evaluate market trends, assess macroeconomic factors, and understand the impacts of monetary and fiscal policies on investment strategies.
Understanding of how AI-driven systems are used in algorithmic trading and risk management, including the quantitative evaluation of automated strategies to reduce market volatility.
The ability to organize, analyze, and visualize data effectively, enabling informed decision-making in domestic and global financial markets through the use of cutting-edge computational tools.

Advance Your Career

BU MET’s Financial Management master’s prepares you for a wealth of different roles, such as financial analyst, investment analyst, finance manager, financial advisor, equity research analyst, financial planner, wealth analyst, equity/credit research analyst, and mergers and acquisitions analyst, among others.

Recent graduates have found job opportunities and career paths at companies such as:

JP Morgan
HSBC
Goldman Sachs
Broad Institute of MIT and Harvard
Pratt & Whitney
Pacific Gas and Electric Company (PG&E)

AllClear Aerospace & Defense
PwC
Delaware North
Copa Airlines
Youth Today

Take Advantage of Career Resources at BU MET

You will find the support you need in reaching your career goals through MET’s Career Development office, which offers a variety of job-hunting resources, including one-on-one career counseling by appointment for online students. You can also take advantage of tools and resources available online through BU’s Center for Career Development.

Financial Management Faculty

Irena Vodenska

Professor of Finance

Director, Finance Programs

Chair, Administrative Sciences

Lin Ge

Associate Professor of the Practice, Administrative Sciences

Coordinator, Financial Management

Christopher Athaide

Assistant Professor, Administrative Sciences

San Chee

Senior Lecturer, Administrative Sciences

Ivan F. Julio

Assistant Professor, Administrative Sciences

Maruška Vizek

Visiting Associate Professor, Administrative Sciences

Interested in Learning More?

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Online Master of Science in Financial Management, Artificial Intelligence Applications Concentration

At a Glance

Unlock Career Success with AI-Driven Financial Modeling and Advanced Analytics