In the spring 2026 semester, a team of graduate students built a machine learning model to predict whether a beauty consumer was more likely to shop at Sephora or Ulta. They didn’t stop at data modeling, though; they translated those predictions into a targeted marketing strategy for a successful existing beauty brand, complete with a detailed cost-benefit analysis.
The final result? A projected $167,575 in profit at a 14.45% ROI, outperforming both broad-reach and single-channel targeting strategies.
They came to these conclusions not in a corporate office or a high-priced consultancy, but in UVA McIntire’s M.S. in Commerce program.
A result like that one, real business value generated before graduation, is not a lucky break. It is what happens when faculty deliberately engineer the conditions for it. The 10-month degree program is built on a simple but demanding premise: that students should be able to walk into a job and contribute something meaningful on day one. That intention shapes everything from how faculty structure course assignments to the types of problems they ask students to solve.
Across analytics, project management, data visualization, finance, communication, and more, M.S. in Commerce faculty are deliberately closing the gap between classroom work and professional practice, teaching students first to analyze hard problems, then to communicate what they find, and finally to negotiate the outcomes those findings demand.
Real Problems, Real Data, Real Stakes
Professor Brent Kitchens’ Foundations of Machine Learning and AI makes that ambition explicit.
“My course is project-based,” says Kitchens. “In it, students identify an organizational or societal problem, obtain data, train predictive models, use their predictions to recommend courses of action that address the problem, and evaluate the value provided from their solutions.”
In addition to using consumer marketing to optimize digital ad targeting for a beauty company, student teams tackle problems that are entirely unsimulated, spanning critical global industries. In infrastructure and global development, a group built a targeted preventative maintenance program to predict and prevent water well failure in Tanzania; the healthcare sector saw students predicting hospital readmissions to enable early, life-saving clinical interventions; projects in finance and sports analytics ranged from creating capital investment strategies for personal loan portfolios to building performance-based loss-of-value insurance models for high-profile NFL draft prospects.
Each project runs through a full CRISP-DM (Cross-Industry Standard Process for Data Mining) cycle, the analytics industry’s standard workflow. Students move from a deep understanding of the business problem and the data preparation it requires through modeling, evaluation, and a final set of recommendations.
Kitchens structures the project in phases that progressively shift the audience and the register of communication. The progress report is written for an analytics manager, someone who needs enough technical detail to evaluate and replicate the work. The final presentation is a consulting-style delivery aimed at executive management, where teams must distill months of analysis into a story that drives decisions.
“Similar project formats have been increasingly used in interviews and day-to-day work,” Kitchens notes, pointing to why the design of his course mirrors what many graduates will face almost immediately on the job.
Data Visualization and the Language of the Boardroom
Generating a strong analysis, though, is only the first step. An insight changes nothing until someone with the authority to act is persuaded to act on it. Turning analysis into persuasion is the skill at the center of Professor Chris Maurer’s coursework.
In his Data Aggregation and Visualization course, the real challenge is not simply to find an insight but to make a business audience see it. To get there, students pull data from multiple real-world sources, clean and integrate it in Tableau Prep, and then build visualizations that tell a coherent business story. The deliverables include both a written memo and a live presentation; the dual requirement is deliberate, because most professionals spend their careers moving between written reports and verbal presentations, and knowing how to reformat an insight for each medium is its own distinct skill.
In his Essentials of Project Management course, Maurer takes a different but equally practical approach, and he opens with a scenario that carries immediate stakes.
Teams simulate planning a service-learning trip for the entire M.S. in Commerce cohort, forcing them to navigate stakeholder management, budget constraints, scope creep, and logistics coordination. Because the assignment mirrors the program’s Global Immersion Experience (GIE), its signature international capstone, students operate within a realistic operational context rather than an abstract exercise. To manage that project, each team selects a tool, such as Jira, Asana, Trello, or ClickUp; learns it independently; and uses it to run the work from scoping through completion. The final deliverable is an objective whitepaper and a recorded podcast review of the platform they chose.
“My goal is to expose them to project management tools such that they have information to use when selecting an appropriate tool to help them work on projects in their career,” says Maurer.
The result is that students don’t simply study project management in the abstract. They finish having run a complex, multi-stakeholder project from start to finish, with a considered point of view on the tools professionals actually rely on to keep that kind of work on track.
Negotiation at the Highest Stakes
Persuading an audience that shares your goal is one challenge; negotiating with people whose interests run directly against your own is a harder one. That is the terrain of Professor Gayle Erwin’s Finance Track sequence. For Finance Track students, Erwin structures her two courses around a direct line from foundational preparation to advanced simulation. While the fall course focuses on building the technical analytical framework and interview readiness that finance roles demand, the spring course shifts entirely into high-stakes negotiation simulations modeled on real deal structures.
One simulation centers on an intensive mergers and acquisitions scenario, while another simulates a complex corporate restructuring. Teams are assigned specific corporate roles, such as an activist investor group or a company’s distressed board of directors, with each team given asymmetric, conflicting sets of proprietary information.
The design intentionally mirrors the competing incentives that define many real transactions. For example, in the restructuring simulation, the student team representing the creditors might press for immediate liquidation to secure their collateral, while the student team representing management must leverage projections to argue for a debt-equity swap. Ambiguity requires critical thinking at the highest level since no team has everything they need, just like any professional in an actual M&A process. Students have to evaluate what information they hold, what the other side likely wants, and how to structure an agreement under intense time pressure. That experience matters to the firms that hire them, which increasingly expect junior employees to contribute inside live deals, not just build the models that support them.
Ultimately, students learn that a successful deal isn’t about running a spreadsheet; it’s about reading the room and finding a middle ground where both sides can sign on. Those simulations develop exactly the kind of strategic judgment that many finance employers say is hardest to teach on the job.
A Consistent Design Philosophy
What connects the work of Kitchens, Maurer, and Erwin, along with the progression from analyzing problems to communicating findings to negotiating outcomes, is a shared conviction that the most valuable thing a graduate program can offer extends well beyond knowledge and into confident, practiced competence. Their courses are designed with the specific formats, audiences, and pressures of professional life in mind.
It is why the team behind the Sephora-versus-Ulta model was already generating measurable business value months before anyone handed them a diploma. M.S. in Commerce students don’t wait until their first job to start solving complex business problems; faculty design their courses so that the work begins during the program itself. By the time graduates arrive at that first job, they aren’t starting from scratch; they’re continuing to build on the skills they’ve already applied to problem-solving.
