Project Associate (Energy & Environment Lab)

University of Chicago
Chicago, IL, United States
Position Type: 
Full-Time
Organization Type: 
University/Academia/Research/Think tank
Experience Level: 
Entry Level (0-2 Years)
Degree Required: 
Bachelor's (Or Equivalent)
Apply By: 
ASAP

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About the Unit

The University of Chicago Energy & Environment Lab (E&E Lab) partners with agencies at the federal, state and local level to identify, rigorously evaluate, and help scale programs and policies that reduce pollution and improve environmental outcomes, while ensuring access to reliable and affordable energy. The E&E Lab uses natural experiments, randomized control trials, behavioral economics, and machine learning to help policymakers identify and generate evidence around innovative approaches to their most pressing environmental and energy-related challenges. Urban Labs partners with cities to identify and rigorously evaluate the policies and programs with the greatest potential to improve human lives at scale. Urban Labs’ evidence-based approach gives policymakers and practitioners the knowledge they need to effectively achieve the greatest social good per dollar spent.

Job Information

Job Summary:

The University of Chicago's Energy & Environment Lab is seeking a Project Associate with strong research, methodological, and programming skills to support large-scale environmental policy research projects. The Associate will work on a growing portfolio of projects designed to evaluate the effectiveness and impact of promising energy and environmental interventions. The successful candidate will have experience with data management, econometrics, and statistical modeling. The Associate will contribute to all facets of data collection processing, model development, and implementation. This position requires an individual who is able to work as part of small research teams, and on multiple projects concurrently, while also being self-directed and independent. The position offers the opportunity to work directly with leading policy researchers and faculty at the University of Chicago and other universities, and policymakers in state and local environmental agencies.

Responsibilities:

  • Assist the research team with data collection, management, and analysis. Responsibilities include documenting incoming data, cleaning and preparing datasets for analysis, matching, sampling, and conducting randomization across multiple projects.
  • Contribute to building traditional statistical models and machine learning algorithms for a variety of research projects.
  • Prepare results for memos, spreadsheets, and presentations targeting both policymakers and academic audiences.
  • Assist with the coordination of research activities, communication with partner agencies, and managing project deliverables.
  • Assist in writing grant proposals, prepare human subjects protocols and amendments for IRB.
  • Conduct thorough and critical reviews of relevant literature.
  • Other duties as assigned.

Competencies:

  • Strong interest in environmental policy required.
  • Strong background in applied statistics & modeling required.
  • Strong written and verbal communication skills required.
  • Ability to manage multiple projects simultaneously and meet tight deadlines required.
  • Excellent organizational skills and attention to detail required.
  • Ability to work both independently, in a self-directed manner, and as a team member required.
  • Ability to work discreetly with sensitive and confidential data required.

Additional Requirements​​

Education, Experience, or Certifications:

Education:

  • Bachelor's degree in economics, statistics, or other relevant social/mathematical science field required.
  • Coursework in econometrics and/or mathematical statistics required.

Experience:

  • A minimum of one year of relevant research experience required. Experience gained in school counts towards requirement.

Technical Knowledge or Skills:

  • Knowledge of STATA, SAS, R or other programming languages required.
  • Experience working with large and complex datasets strongly preferred.
  • Experience working on field experiments / randomized controlled trials preferred.
  • Experience working with UNIX servers preferred.