The University Data Office at Yale University, led by our new Chief Data Officer (CDO), is on an exciting multi-year journey to transform how data is leveraged across the university as a strategic asset. The newly established University Data Office will play a critical role in promoting the use of data across the university in decision-making, safely utilizing advances in AI, and ensuring the security and privacy of the university’s data. Yale has a wealth of data from its teaching and research activities, but the effectiveness of utilizing data to make informed decisions is limited today by a fragmented data environment and cross-domain analytics conducted mostly on an ad hoc basis. The mission of the University Data Office is to develop a cohesive data strategy and federated governance model that will enable integrated insights for deans and other key stakeholders at the university.
As an early hire in the new University Data Office, the Product Management Fellow, Data Solutions, will have the opportunity to be a part of this transformative initiative to shape the future of data-driven insights at one of the world’s most prestigious academic institutions.
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Role Description
We are currently hiring for a Full-time Fellowship, focusing on Product Management, Data Solutions. This is a salaried, full-time position planned for two years in length. Longer‐term roles at the university are possible post-fellowship. This position is open to applicants who will have graduated from Yale by the summer of 2025. Compensation is $85,000-$95,000 per year depending on qualifications.
In this role, the successful candidate will approach the creation and adoption of data solutions for university leaders through a product management and data analysis lens. The focus will be on understanding users’ data needs and the context in which the data will be used to drive decision-making, prototyping data reporting solutions to enable iteration on user needs, coordinating with ITS teams on the build-out of scalable production-level data solutions, and engaging with users post-release to drive adoption and usage.
Click here to apply.
Desired profile:
- Practical and results‐oriented: First and foremost, you care about solving problems. You take a hypothesis‐driven approach and are willing to iterate to get to a workable solution.
- Agile with Data Analysis: You must love applying logic to problems and have an inherent comfort with data, data systems, and data analysis. You come from a computer science, STEM or quantitatively focused field, and you are comfortable rolling up your sleeves with data to produce impactful insights.
- Attentive to detail: You have the highest standards for your work and always strive for zero defects. You extend this mindset to the data you work with, identifying gaps and quality issues that need to be solved collaboratively with ITS and other stakeholders.
- Empathy & “Customer-oriented” mindset: You listen well and understand others’ perspectives. You seek to understand how data solutions will enable decisions, think deeply about the user experience of engaging with data analytics, and represent the “voice of the customer” in your work on data solutions.
- Collaborative and relationship‐oriented: You love solving problems in a team environment, and easily build productive and trusting relationships with stakeholders.
- Mission-driven: Committed to and passionate about Yale’s mission and the advancement of higher education.
Key responsibilities, Include but are not limited to:
- Collaborate closely with stakeholders including cross-functional leaders such as deans and provosts to understand their cross-domain data needs.
- Work closely with data stewards and ITS teams to understand the accessibility and availability of data in various domains (finance, HR, space, student, etc.) that is required to create new data solutions.
- Collaborate with Office of Institutional Research on potential external datasets (e.g. benchmarking vs. Ivy+ peer group) that can enrich and contextualize data solutions
- Prototype data reporting solutions, using a combination of data analysis and reporting tools: R and/or Python, PowerBI, Excel, etc.
- Iterate with both end users and ITS teams throughout prototype development to ensure that the approach both addresses the users’ needs and is replicable at scale.
- Identify data quality issues, and seek to understand the source (data creation, transformation, maintenance, etc.).
- Consider various end users’ data and reporting access needs, enabling collaboration with ITS on data governance and security/privacy policies applicable to data solutions.
- Work with ITS to develop data solution roadmaps that consider the who/what/where/when/how of data solutions, timelines for building and releasing data solutions, project milestones, etc.
- Support documentation and training on data solutions, pre and post release
- Facilitate hands-on working sessions with data users to support adoption and usage of data solutions post-release.
Additional details:
- Fellows receive a salary commensurate with qualifications in the range of $85k – $95k with medical, dental, and vision insurance, as well as other postdoctoral/postgraduate associate benefits
- Work location policy: on-site at least 3 days a week.
Click here to apply.
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