The Capstone program has served businesses of all sizes, from startups to Fortune 100 firms, and from for-profit to not-for-profit organizations. There is no charge to the client sponsor if your project is selected, and we encourage firms and organizations from all industries to apply. In fact, you may sponsor multiple Capstone projects, and really shorten that to-do list.
Your project can be accomplished virtually, in-person, or as a combination of both. There is no need to incur the costs of travel to our campus.
We consider projects through the fall to have sufficient time to finalize legal and data transfer requirements. Project work occurs during our Spring 2 term, which runs from mid-March through early May.
Capstone Project Sponsor Commitments
- Provide an NDA/DUA to be signed by the student team.
- Securely transfer (or provide access) to the required data in a timely fashion.
- Assign a liaison who will be the team’s primary point of contact
- Meet with the student team approximately once per week from from mid-March through early May to provide technical and strategic guidance, as needed.
- Provide feedback of the final deliverables to the student teams.
Each Capstone project is specific to one of the four industry/function specific tracks in the MQM: Business Analytics program. In addition to a core business foundation curriculum that all MQM:BA students receive, these tracks are areas of interest to students who select the one track that they will focus on during the program and in their career. Project objectives from each track on which previous MQM: BA students have worked include:
- Develop a tool that forecasts the likelihood of bull/bear markets over various horizons, and across multiple asset classes/segments.
- Using options to construct convexity overlays, explore whether investment opportunities can be identified from the shape of the US Treasury yield curve.
- Identify the main drivers of client sales in order to incorporate these drivers into KPI’s appropriate to evaluate sales efforts.
- Using natural language processing, validate pain points from a feedback survey to ensure the correct categories of issues are being identified in support requests.
- Develop a machine-learning model to identify potential waste, fraud, and abuse in identification systems used for building access, consumer purchases, and identity management.
- Create an anomaly-detection system that identifies possible data exfiltration and unauthorized access in a cloud-based application.
- Create a scheduling algorithm to more efficiently match patient needs and doctor performance for specific types of medical procedures.
- Using nationwide installation data, analyze the potential to use a specific FHA financial product to aid low- and middle-income families in acquiring solar panels.
Ensure that you can deliver on all of the commitments listed above for the project you'd like to undertake with students.
Once you've defined the objective and determined the parameters of the project, email Jeremy Petranka to schedule a time to discuss your project.