Job Summary

RTI International has an opening for an economist / modeler in the agricultural and environmental economics practice within the Center for Applied Economics and Strategy (CAES). Our team in CAES draws on a range of quantitative and qualitative skill sets to produce high quality research for government agencies, foundations, and non-profit organizations. Our work requires implementing the best available theory and methods in assessing environmental and economic outcomes to report rigorous and actionable results to our clients.

 

The successful candidate will work with a team of economists, engineers, and analysts to assess the environmental and economic consequences of a broad range of domestic and international policies, programs, and technological innovations within the land use sector, including agriculture, food, and forestry. They will do this by building new models or utilizing existing, industry standard models, and methods.

The successful candidate will have training in economics or related disciplines and experience applying modeling best practices in the maintenance and enhancement of core datasets and identifying fit-for-purpose technical approaches in partnership with senior staff and project teams. The role will execute quantitative analyses and clearly articulate results to a wide range of audiences. We seek a candidate with a clear interest in agricultural and environmental economics, a versatile technical skill set, demonstrated GAMS programming experience as well as R and/or python programming experience, and strong writing skills.

Responsibilities

The successful candidate will be expected to contribute to the following task areas:

· Conduct literature reviews to identify best available data and/or best practices for data processing and analysis

· Design, execute, and communicate data analysis and research

· Lead the maintenance of core datasets to our analyses in replicable code and version-controlled repositories (i.e. via GitHub)

· Contribute to the development of national and global economic models, incorporate underlying datasets and understand data availability and limitations.

· Develop post-processing routines for analyzing, reporting, and visualizing model outputs.

· Visualize data in clear and compelling graphics including dynamic implementations (e.g. in Tableau or R markdown).

· Maintain currency with key issues and concepts in environment topic areas including climate change mitigation and adaptation in the energy, agriculture, food, transportation, waste, and forestry sectors. Knowledge of other agricultural and environmental issues (e.g. water resources, criteria pollutants) will be valued.

· Work with a wide variety of data content and formats, including spatial data (e.g. remote sensing), energy data (e.g. physical units produced/consumed), economic data including industry, household, and national accounts information, purchase data, market price data.

· Collaborate effectively with project team members, and with external scientists.

· Manage workflow in a timely, realistic, and cost-effective manner to meet client expectations.

· Contribute to grant, cooperative agreement, and contract proposals.

Present research methods and findings via technical reports, journal articles, and presentations

Qualifications

Qualified applicants should have the following:

· Master’s degree in a relevant field or a Bachelor’s degree and three years of relevant work experience.

· Demonstrated experience developing and programing linear optimization models and working in optimization model frameworks.

· Demonstrated experience collecting, processing, managing and analyzing data, including experience with and knowledge of best coding practices for one or more of the following: GAMS, R, Python, Julia , or related programs.

· Demonstrated interest in agricultural and environmental resource issues.

· Excellent verbal and written communication skills, including ability to communicate complex issues to a wide range of audiences, and a track-record of publications and/or quantitative analytical outputs. If selected to interview for the position, writing samples will be required, preferably with a focus related to one of the topic areas above.

 

Preferred

· At least 1 year of relevant work experience desired.

· Demonstrated experience with geospatial analysis.

· Demonstrated experience developing and programming machine learning or other types of models for predictive analysis.

· Experience with partial equilibrium economic models, including linear optimization models, or other types of empirical models, preferably in GAMS.

· Experience working on topics related to agricultural, energy, environmental, or natural resource economics.