Upload a copy of your resume. The purpose of this document is to provide a snapshot of your education and professional achievements in your career. Use a standard (i.e. Times New Roman or Arial), 12-pt. font for your 1-2 page resume.

Education Requirements

Students are required to hold a four-year undergraduate degree or equivalent from an accredited institution.

While there are no additional educational requirements, if you have questions about our typical class profile and experience, contact our admissions team at mspm@cmu.edu.

Transcripts

Transcripts uploaded during the application process are considered “unofficial.” What makes a transcript "unofficial" is that you have it in your possession instead of us receiving it in a sealed, stamped envelope directly from your university.

All candidates are required to upload legible, scanned/digitized copies of their unofficial transcripts, not web transcripts*, and degree certificates which include the following:

• University Transcripts: All transcripts are copies of actual university transcripts (not web transcripts), usually on watermarked paper with a seal, etc.
• Degree Name: If you earned a degree, the name is on the transcript (i.e. Bachelor of Science, Master of Arts, etc.).
• Degree Conferral Date: If you earned a degree, the date the degree was awarded is on the transcript.
• Degree Certificate: If you earned a degree and the degree name/conferral date are not on the transcript, you must upload a copy of your degree certificate which includes this information. This cannot be a provisional certificate; it must be final. Still unsure what to submit? See sample degree certificates.
• Grading Scale: Include for every university so we know what the grades mean. Often on the back of the transcript; otherwise, contact the university to obtain. Still unsure what to submit? See sample grading scales.
• Official Translation: If the transcript is not in English, upload both the transcript in the original language and the official translated copy so that we can read it.

View a sample of a web transcript that you should avoid submitting.

*A web transcript is anything obtained from an online student portal, downloaded from your student record, or retrieved online.

Please ask your GMAT, GMAT Focus, or GRE testing agency to send us your official score, so we can verify what you provide on your application.

A couple of important points:

• GMAT and GRE scores are valid for five years. Yours must still be valid when you submit your application.
• Request that the official score be sent to us using the following codes:
  • Graduate Management Admissions Test (GMAT) - Select Carnegie Mellon University Tepper School Master of Science in Product Management
  • Graduate Record Examination Tests (GRE) Program Code 4883

If you wish to apply for a GMAT/GRE waiver, you must do the following:

Submit a letter to the admissions committee (via an upload in your application) that addresses the following:

• Please discuss your undergraduate GPA scores and any other degree GPA. For a waiver to be granted we are only seeking those with exceptionally high GPA achievement.
• Please also share any remarkable academic achievements we should be aware of.
• Please share with us if you have an advanced master’s degree. Is it in a STEM-related area? Are there particular courses that demonstrate your capability in succeeding in the MSPM curriculum?
• Please share if you have recognized certification in product management, e.g. ISPMA, Pragmatic Institute, AIPMM, Certified Scrum Product Owner, Certified Product Manager (280 Group), Certified Innovation Leader Credential, ProductSchool, Black Bolt Product Management, etc.

Also:

• Please highlight if you have 10 or more years of professional working experience. Please be specific about your roles and job content relative to a role in product management.
• Please share if you had held the role of product manager and for how many years. Please describe the job and role beyond what is on your resume/CV and be specific about your accomplishments in this role that are relevant to the MSPM degree.

Test Courses:

Test waiver applicants may need to complete the following coursework and show proof of completion:

• CS50: Introduction to Computer Science
• Introduction to Python: Fundamentals
• Become a Product Manager
• Introduction to Finance, Accounting, Modeling and Valuation

Upon submission of your application, the waiver request will be reviewed, and you will receive a response to the waiver request via email within 10 business days of the application deadline. Please note, only complete applications will be reviewed for test waivers.

Candidates are required to demonstrate a level of competence in English to meet the admissions requirements of the university. You are required to take a TOEFL, IELTS, or Duolingo exam unless:

• You attended an undergraduate institution, earning a bachelor’s degree, where the sole language of instruction was English.
• You earned a graduate degree where the sole language of instruction was English. (Although not required, we do recommend that you take the English Language Proficiency exam.)

You must request that the official score be sent from the testing agency to our program for us to verify the score entered into the application. Request that the official score be sent to us using the following codes:

TOEFL Program Code: Institutional Code = 2074; Organization: Carnegie Mellon University, Graduate Business Organization

• Pro Tip: The recommended TOEFL score is 25 on each section of the Internet-based test. Reading: 25, Listening: 25, Speaking: 25, Writing: 25
• Pro Tip: For the new, TOEFL iBT, we recommend at least a 5 in the overall score and subscores of 5 and above in each section.

IELTS Program Code: Select Carnegie Mellon and the Tepper School of Business

• The recommended IELTS score is 7 overall and 7 in each band. Listening: 7, Reading: 7, Writing: 7, Speaking: 7, Overall Band: 7

Duolingo Program Code: Select Carnegie Mellon University – Tepper School of Business

• The recommended Duolingo English Test (DET) score is 120 overall.

TOEFL and IELTS scores are valid for two years and must be valid at the time you submit your application.

If you earned a degree from a non-U.S. institution, your academic documents should state that the sole language of instruction for the entire university was English in order to be eligible for a TOEFL/IELTS/Duolingo waiver. If your academic documents don’t include this, you should upload an official letter from the University Registrar indicating English as the mode of instruction for the entirety of the degree.

There are two required essays (maximum 500 words) for all Tepper MSPM applicants:

1. The Tepper community is dynamic and unique with students who strive to be collaborative, supportive and inclusive. Please provide an example of when you experienced or created an inclusive environment and how you will use that experience to help members of the community reach their full potential.
2. Share a time you made a mistake at work. Provide context that you feel would adequately describe how you felt when this occurred, what you did when you realized the mistake and what, if anything, did you learn from this experience.

Optional essay: Use this essay to convey any important information you may have otherwise not been able to communicate. This may include unexplained resume gaps, your reason for selecting the recommender you chose, or if you are applying again, how your candidacy has improved since your last application.

We know this is an important component of your decision to attend business school. We take it seriously as well. Please describe your post-MSPM career goals and why you chose them as your goals.

It would be helpful to consider the following information in your response:

• You have up to 2 minutes to respond to this question.
• Please be as specific as possible. If you have not yet identified specific companies, that is okay. Just tell us what interests you for your next role or company. What about the industry, company, or functional role is appealing to you?
• If you have any criteria you are using to evaluate career opportunities, please share those as well. We may have great opportunities to add to your list.
• How does this post-MSPM career goal relate to your long-term career plan?

Please select two people familiar with your work and/or leadership skill. We prefer that you select supervisors, but you can also include professors, coaches, mentors, or coworkers. Please give us their email contact information on your application, and we’ll reach out to them with a request to submit their letters online.

We use the GMAC Common Letter of Recommendation (LOR). The Common LOR is intended to save you and your recommender valuable time by providing a single set of recommendation questions for each participating school. This allows your recommender to use the same answers for multiple letter submissions, alleviating the workload of having to answer different questions for each school multiple times. You benefit because it makes the ask for several different letters to be written on your behalf much easier.

A non-refundable $125 application fee is required of all applicants. This fee can be paid online using a credit card at the time of submission.

Once you have completed your online application, if you have any supporting documents, they should be uploaded directly to your application via your application status page in the application portal.

If you have submitted all the application components, it isn’t necessary to send anything else to us at this point. Upon admission, you’ll need to send your official transcripts/academic documents. These details will be included in the admission letter, so no need to worry about it now.

Admissions interviews are granted at the discretion of the admissions committee after an initial review of your application. You will receive additional information about the interview process at the time of the invitation.

We welcome applicants from around the globe and encourage non-U.S. citizens to apply to our Masters of Science in Product Management (MSPM) program.

Applications from international candidates are accepted through all application rounds, but we encourage international candidates to submit their applications in Round 1 or Round 2.

Certification of Financial Resources

As an applicant from a foreign country, you will be required to verify financial resources equal to the total cost of tuition and living expenses for the duration of the program. If admitted, students will be required to submit the following forms with appropriate supporting documentation in order to obtain a valid visa for entering the United States.

Graduate Student Financial Statement including official documentation such as personal bank statements and letters of support from any sponsoring organizations.

If sponsored by an employer or other third party, an Affidavit of Support including official documentation such as bank statements and verification of sponsor support.

Visa Regulations

Visa regulations can be quite complex, and it is the applicant’s responsibility to be aware of the regulations. Carnegie Mellon University has a foreign student advisor to assist applicants in visa matters, and we strongly recommend that you use this service.

The contact information for any applicant who would like to contact our foreign student advisor is:

Office of International Education
Carnegie Mellon University
Cyert Hall, First Floor Atrium
Pittsburgh, PA 15213, USA
412-268-5231
Email: oie@andrew.cmu.edu

The United States' visa-granting authority in the country of origin, ordinarily the United States Embassy, requires proof that sufficient funds are available to a student to cover both years of study before he/she is granted either the student visa (F-1) or an exchange visa (J-1).

BaseCamp sets the stage for productive communication, collaborative learning, and success throughout the MS in Business Analytics program. As with each on-campus visit, students stay at the same hotel and have lunch with faculty members and each other.

During BaseCamp, faculty members provide students with a high-level overview of the MSBA program and bring in a range of Tepper School staff, including members of the recruitment team, to supply information about financial aid, career planning, and student services. Other BaseCamp activities include a company visit, campus tour, and social event in Pittsburgh.

Discover the world of analytics at Carnegie Mellon University, the birthplace of AI and data-informed management science. This immersion experience offers a window into the different ways in which Carnegie Mellon faculty and staff impact this cutting-edge field.

From applications of analytics in athletics to using analytics to manage an organization, this on-campus experience gives you insight into the expanding ways in which data and analytics are applied in the business world today. You will also have the opportunity to engage in professional development workshops with faculty and our Accelerate Leadership Center.

Prior to kicking off your semester-long capstone course, you come to campus for a Capstone Experience Weekend. During this weekend, you meet your faculty and company sponsor and gear up for your project. At the end of the semester, you present your findings to your sponsor company, marking the end of the MSBA program.

Analytics expertise is in high demand across every industry, creating exceptional opportunities for Tepper School MSBA graduates who excel at transforming data into strategic advantage. The U.S. Bureau of Labor Statistics projects 36% growth for data scientists and a 23% increase for operations research analysts through 2033.

MSBA graduates advance into senior roles like strategic pricing analysts, global development specialists, and business development directors across finance, tech, consulting, and manufacturing. Recent employers include:

• Bank of New York Mellon
• Capital One
• Deloitte
• EY (Ernst & Young)
• Google
• Kantar
• McKinsey & Company
• The Walt Disney Company
• Wells Fargo & Company

Our Masters Career Center pairs you with a personal coach who is an expert in your target industry. We serve a small, intentionally selected student body, which is why we can offer exceptional, tailored support for your goals.

• Programming in R and Python
• Introduction to Probability and Statistics
• Managing People and Teams
• Business Fundamentals
• Experiential Learning

• Business Communication
• Statistical Foundations of Business Analytics
• Machine Learning Fundamentals
• Modern Data Management
• Experiential Learning

• Optimization
• Data Exploration
• Elective
• Elective
• Capstone

• Business Value for Integrative Analytics
• Machine Learning for Business Applications
• Elective
• Elective
• Capstone

• Programming in R & Python
• Introduction to Probability & Statistics
• Campus Experience: BaseCamp (Optional)

• Statistical Foundations of Business Analytics
• Business Fundamentals

• Modern Data Management
• Data Exploration & Visualization

• Machine Learning Fundamentals
• Business Communication
• Campus Experience: Analytics Immersion (Optional)

• Optimization for Prescriptive Analytics
• Data Analytics in Finance

• Operations and Supply Chain Analytics
• Ethics and AI

• Organizations to Managing Teams and People
• Business Value Through Integrative Analytics

• Machine Learning for Business Applications
• Optional Elective
• Campus Experience: Capstone Overview (Optional)

• Capstone
• Analytical Marketing

• Capstone
• Optional Elective

This course introduces tools for decision-making under uncertainty, ranging from the fundamentals of probability theory, decision theory, and statistical models to basic software for data analysis. Topics include statistical independence, conditional probability, Bayes theorem, discrete and continuous distributions, expectation and variance, decision trees, sampling and sampling distributions, interval estimation, correlation, and simple regression.

This course provides an introduction to programming in Python and R, two of the most popular languages for data analytics. The course will cover basic concepts such as conditionals and loops, but also functions and program modularity, as well as algorithms and data structures.

This course provides a basic introduction on general business management. Topics include organizational structure, the role of different business domains in an organization (accounting, finance, operations, and marketing), and how they relate.

The objective of this course is to help you learn to analyze data and use methods of statistical inference in making business decisions. This course focuses on the application of fundamental concepts from Probability and Statistics to drawing inferences from data. Topics will include Bayesian modeling, multivariate analysis, causal inference, A/B testing, and experimental design, with special emphasis on diagnostics and model-building techniques appropriate to the study of real-world data. Assignments with applications to real-world data are an integral part of the course.

The focus of this course is on managing and retrieving data of all types (structured, semi structured, or unstructured), from both technical and business perspectives. The course topics include relational data management systems, theory of databases and models (CAP, ACID, Distributed Computing and Storage), Document (MongoDB), and other models for Big Data. The course also provides a basic conceptual introduction to Hadoop, Map-reduce, Hive, Apache Spark (in general, the big data architecture).

This course provides an introduction to the principles and techniques for data visualization. Students will learn visual representation methods and techniques that increase the understanding of complex data and models. Principles will be drawn from statistics, graphic design, cognitive psychology, information design, communications, and data mining. Specific topics that will be covered include design principles for charts and graphs, common visualization tools (Tableau, Excel, and R), effective presentations, dashboard design, and web-based visualizations.

In this course, we explore common machine learning techniques and think about the application of these techniques to both structured and unstructured datasets found in business. Specific topics include Linear Regression (logistics regression, k-nearest neighbors, and SVMs) and Unsupervised Learning (Principal Components and Clustering Methods: Hierarchical, partitioning, and probabilistic).

This course continues the introduction of machine learning techniques with a particular emphasis on business applications. Specific topics include Model and Variable Selection Model and Variable Selection (Overfitting and Overconfidence, Bias-Variance Tradeoffs; Information Criterions and Cross-Validation; Model Averaging and Ensemble Learning; Feature Selection; Regularization, Shrinkage and LASSO Estimators), Nonlinear Prediction Methods (Tree-Based Methods: Decision Trees and Random Forests; Regression Splines; Kernel Methods and Gaussian Processes), Modeling with Latent Variables (Hidden Markov Models; Graphical Models).

Mathematical optimization technology is key to turning data into better decision-making. The application of large-scale optimization models can bring a critical competitive advantage to many firms. This course focuses on developing such optimization models for operational and strategic decision making, with applications that include vehicle routing, employee scheduling, network design, and capacity planning. Methodologies include Linear programming, integer programming, nonlinear programming, constraint programming, heuristics, and column generation.

This is an integrative course that charts the path to value from analytical modeling for business problems. Building on a set of multidisciplinary cases cross-cutting across functional areas of business, this course integrates the three increasing levels of analytics involved in reaping business value from data in a given problem: the descriptive phase of inferring key features and relationships in the problem, the predictive phase of forecasting outcomes of short-term tactical actions, and the prescriptive phase of long-term planning based on analytics.

This course introduces students to both the micro and macro perspectives of organizational behavior and theory. At the micro-level, it covers factors for working in and managing an effective work team, including building teams, team contracting, team coordination, and team creativity. Macro topics include team networks, informal and formal organizational networks, communication networks, and innovation culture.

The course will address several areas of finance that rely heavily on data analytics, including 1) High Frequency Trading and Market Micro-structure, 2) Quantitative portfolios and Asset Management, 3) “Smart” Beta and Performance Analysis, and 4) Credit Analysis. The class uses tools from statistics, data mining (machine learning), and NLP/text-mining.

Operations and supply chain analytics is concerned with the development and application to data of business analytics tools to support high-impact strategic, tactical, and operational decisions within both manufacturing and service firms. Topics include supply chain design, demand forecasting, inventory planning, sales and operational planning, revenue management, staffing in service organizations, and healthcare management. The underlying feature in these applications is managing the risk that arises from supply and demand mismatches with the goal of maximizing enterprise value. The course emphasizes how sophisticated and holistic implementation of the operations and supply chain analytics toolbox, integrating descriptive, predictive, and prescriptive analytics techniques, can be an essential lever to increase or sustain a firm’s competitive advantage.

Marketing has become much more quantitative and data-intensive in recent years. Strategies like interactive marketing, customer relationship management, and database marketing push companies to utilize the information they collect about their customers to make better marketing decisions. Marketing transaction data — which is a common type of Big Data — often forms the core set of information used for making marketing decisions. This course focuses on how analytical techniques from data mining, machine learning, and statistical modeling can be applied to solve marketing problems. This course focuses on a series of data-intensive case studies to solve marketing problems. Specifically, the case studies considered include pricing decision support systems using retail transaction data, understanding customer churn in the cell-phone market, upgrading freemium customers to paying customers, and lifetime cycles in direct marketing.

This course will be aimed at helping the MSBA students know how to target their future business audiences. Students will learn delivery skills AND will simultaneously learn how to construct arguments and problem-solve for decision-makers and how to understand what these audiences need from them (including superior, peer, and subordinate audience groups). Students will be evaluated on presentation assignments that are relevant to business analytics.

This course will explore the ethical challenges that businesses face when making use of AI, map out policies that have been proposed as solutions to these challenges, and analyze the normative arguments behind these policies. The goal of the course is to acquire the skills necessary to understand the ethical challenges which emerge from AI, and develop responsible corporate practices around these technologies. The course is organized around six core principles for the responsible use of AI: Autonomy, Explainability, Discrimination, Fairness, Benefit, and Responsibility & Control.

Early-career business professionals must demonstrate not only technical skills, but also strong communication, executive presence, and the ability to collaborate across cultures. For MSBA and MSM students, this course offers structured, hands-on preparation for project and job success. Through guided practice and feedback, you’ll learn to tell your professional story, build industry relationships, and strengthen your interviewing, networking, and negotiation skills—while gaining the clarity and confidence to pursue your career goals.