The Applied Data Fellowship is a unique program designed to launch careers at the intersection of data, technology, and public service. In a world increasingly driven by data, this fellowship offers a pathway for individuals to apply their analytical skills to solve significant societal challenges. Hosted by the University of Chicago’s Harris School of Public Policy, the fellowship provides a year of hands-on experience, mentorship, and professional development within mission-driven organizations. This article explores what the Applied Data Fellowship entails, who it’s for, the types of roles fellows can undertake, and the valuable skills and experiences gained.
What is the Applied Data Fellowship?
The Applied Data Fellowship (ADF) is a full-time, one-year professional program that connects highly skilled graduate students and emerging professionals with organizations working on complex societal issues. Unlike academic fellowships that might focus more on research, ADF emphasizes practical application and real-world impact. Fellows are integrated into partner organizations, contributing directly to projects that involve data analytics, artificial intelligence, machine learning, public policy implementation, and operational improvements. The program is ideal for those who want to use data and technology to improve public systems, strengthen institutions, and create measurable social change.
Who Are Applied Data Fellows?
Applied Data Fellows are individuals who go beyond traditional data analysis. They are problem-solvers, strategists, and innovators who combine technical expertise with a dedication to public service and mission-driven work. Fellows often come from top graduate programs in fields such as Public Policy, Data Science, Economics, Statistics, Computer Science, Social Sciences, and Information Systems. While each fellow brings unique strengths, they share a common goal: to use data and technology to address meaningful problems.
Types of Roles Fellows Can Perform
The fellowship offers a variety of roles, allowing participants to tailor their experience to their skills and interests.
Data Scientist or Data Analyst
In this role, fellows focus on extracting insights from large datasets to help organizations make informed decisions. Responsibilities typically include data cleaning and preparation, statistical analysis, building predictive models, implementing machine learning algorithms, developing dashboards, and evaluating performance. Common tools used in these roles are Python, R, SQL, Tableau, and Power BI.
Program Manager
Some fellows take on operational and strategic roles. These positions involve stakeholder management, project coordination, program implementation, performance tracking, and strategic planning. Program managers play a key part in ensuring that data-driven insights are translated into tangible real-world outcomes.
Data Strategist (“Data Shaman”)
This hybrid role bridges the gap between technical and operational domains. Fellows in this position help improve organizational workflows, support implementation efforts, reduce operational bottlenecks, and facilitate the adoption of technology solutions. This role combines analytical thinking with organizational leadership skills.
Technical Skills Valued by the Fellowship
The Applied Data Fellowship looks for applicants with expertise or a strong interest in several key areas. These include programming languages like Python, R, and SQL; data visualization tools such as Tableau and Power BI; and artificial intelligence concepts like machine learning and AI adoption. Data engineering skills, including data infrastructure and management systems, are also valuable, as is experience with geospatial analytics. While not every applicant needs to be an expert in all these areas, strong technical or operational capabilities are highly regarded.
A Fellowship Focused on Learning and Growth
A core aspect of the Applied Data Fellowship is its commitment to continuous learning and professional development throughout the year.
One-on-One Mentorship
Each fellow receives dedicated coaching and mentorship. Mentors assist participants in navigating challenges, building technical skills, expanding their professional networks, developing career strategies, and strengthening leadership abilities.
Weekly Upskilling Workshops
Fellows participate in hands-on training sessions designed to enhance practical skills. Topics often cover advanced analytics, machine learning, data visualization, public sector technology, policy analytics, and project implementation, providing immediate value to their ongoing work.
Fireside Chats with Leaders
Participants gain direct access to leaders from government agencies, nonprofit organizations, research institutions, technology companies, and public policy organizations. These discussions offer valuable insights into leadership, innovation, and career development.
Technology and AI Demonstrations
As AI continues to transform industries, fellows are exposed to emerging technologies through regular demonstrations and discussions. These sessions help them understand AI applications, new tools, public sector technology trends, and responsible AI implementation.
Career Outcomes: Why the Applied Data Fellowship Stands Out
The Applied Data Fellowship has a proven track record of helping participants launch successful and impactful careers. Program statistics show a high retention rate, with approximately 70% of fellows being retained full-time by their host organizations after completing the program. This high retention rate highlights the significant value fellows bring to partner organizations. The program has supported over 200 placements across various sectors and has built a strong reputation over eight cohorts.
Where Fellows Go After the Program
Graduates of the fellowship pursue diverse career paths across multiple sectors. Many find roles in government and the public sector, working on public policy, data governance, and service delivery improvement. Others move into strategy consulting, helping organizations solve complex issues with data-driven approaches. Opportunities also exist within nonprofits and foundations, supporting social impact initiatives through analytics and evaluation. Some graduates pursue research and academia, conducting advanced studies and contributing to evidence-based policy. Additionally, many enter the technology and data industry, developing innovative products, systems, and AI solutions.
Understanding the Selection Process
The Applied Data Fellowship is a highly competitive program, with a rigorous selection process.
Rolling Application
Applications are accepted throughout the year, allowing candidates to submit their professional background, technical qualifications, relevant experience, and mission-driven interests at any time.
Strategic Profile Review
Unlike many programs, applicants are not immediately interviewed. Instead, their profiles are reviewed against the current needs of active partner organizations. Candidates are invited to proceed only when there is a strong alignment between their expertise and available projects.
Interview Sprint
Once selected for interviews, the process moves quickly, typically completed within two weeks. Candidates can receive one of three outcomes: an offer to join the fellowship, a rejection, or a “maybe” status if they show potential but do not currently match available projects, with their profile remaining active for future opportunities.
Matching Process
After acceptance, fellows enter a matching phase that generally takes six to eight weeks. During this period, fellows are paired with host
Frequently Asked Questions
What is the Applied Data Fellowship?
The Applied Data Fellowship is a one-year program that connects skilled individuals with organizations working on societal issues, focusing on practical data application and real-world impact.
Who is the Applied Data Fellowship for?
It’s for graduate students and emerging professionals with technical expertise and a strong interest in using data and technology to address public service challenges.
What kind of roles can fellows perform?
Fellows can work as Data Scientists/Analysts, Program Managers, or Data Strategists, applying their skills in data analysis, project coordination, and bridging technical and operational needs.
How does the selection process work?
Applications are reviewed based on alignment with active partner organizations’ needs, followed by a quick interview sprint if there’s a strong match.
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