Computer Science . Machine Learning . Others

and officially incorporated

United States

Presencial

USD 60.000 - 90.000

Jornada completa

14 días+

Una candidatura completa en un minuto

Currículum y carta de presentación personalizados, listos para enviar.

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Ventajas ofrecidas por este puesto de trabajo

Health insurance

Descripción de la vacante

The Applied Data Fellowship (ADF) at the University of Chicago Harris School of Public Policy is a year-long, full-time program that embeds data professionals into mission-driven organizations, spanning government agencies, nonprofits, and foundations.

Analysts may serve as Analysts, Builders, or Data Shamans, moving projects from scoping to full-scale implementation with weekly upskilling workshops and dedicated mentorship from the UChicago ecosystem.

Formación

  • Elite analytical skills and a deep commitment to social impact.
  • Ability to coordinate stakeholders and drive projects forward.
  • Experience building dashboards and implementing AI/ML solutions.

Responsabilidades

  • Move critical projects from scoping to implementation in partner organizations.
  • Coordinate stakeholders across multiple projects and teams.
  • Develop data products and dashboards to inform policy decisions.

Conocimientos

Analytical skills
Stakeholder coordination
Dashboard building
AI/ML implementation

Educación

Graduate degree in public policy
Data science degree

Herramientas

Data visualization tools
Statistical software

Descripción del empleo

USA Computer Science Machine Learning Others

About this opportunity

The Applied Data Fellowship (ADF) at the University of Chicago Harris School of Public Policy is a high-impact program that embeds data professionals into mission-driven organizations. Fellows serve as “Analysts,” “Builders,” or “Data Shamans,” working for one year to move critical projects from initial scoping to full-scale implementation within government agencies, nonprofits, and foundations.The fellowship is designed for individuals who possess elite analytical skills and a deep commitment to social impact. Fellows are not just “crunching numbers”; they are coordinating stakeholders, building dashboards, and implementing AI/ML solutions that drive systemic change. The program provides a “Safety Net” of technical mentorship from the UChicago ecosystem, ensuring that every fellow has the support needed to overcome complex implementation hurdles.The selection process is highly competitive, with a focus on matching specific technical profiles with active partner projects. Beyond the work placement, the ADF offers a year of continuous learning through weekly upskilling workshops, fireside chats with industry leaders, and regular demos of cutting-edge data tools. This combination of hands‑on experience and structured learning makes the ADF a premier launchpad for careers at the intersection of data science and public policy.Target Audience: Graduate‑level analysts, builders, and problem solvers from programs in public policy, data science, economics, computer science, and related fields.Geographic Eligibility: United States (various locations based on partner placements).Tangible Benefits: Competitive stipend, comprehensive health insurance, one‑on‑one mentorship, weekly upskilling workshops, and access to the UChicago technical ecosystem.Application Deadline: Rolling (Applications are reviewed year-round).Program Duration: 1 year (Full‑time commitment).

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