Description

Overview 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. #LI-KW1 EEO & Pay Equity Statements For San Francisco, CA USA Job Postings Only: Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Further information is available here. RTI accepts applications to our job openings from candidates with criminal histories or conviction records in accordance with all applicable laws, including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. The anticipated pay range for this role is listed below. Our pay ranges represent national averages and may vary by location as a geographic differential may be applied to some locations within the United States. RTI considers multiple factors when making an offer including, for example: established salary range, internal budget, business needs, and education and years of work experience possessed by the applicant. Further, salary is merely one element to our offer. At RTI, we demonstrate our commitment to rewarding individual and team achievement through a total rewards package. This package includes (among other things) a competitive base salary, a generous paid time off policy, merit based annual increases, bonus opportunities and a robust recognition program. Other benefits include a competitive range of insurance plans (including health, dental, life, and short-term and long-term disability), access to a retirement savings program such as a 401(k) plan, paid parental leave for all parents, financial assistance with adoption expenses or infertility treatments, financial reimbursement for education and developmental opportunities, an employee assistance program, and numerous other offerings to support a healthy work-life balance. Equal Pay Act Minimum/Range $68,000-$83,000

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

Qualification

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. #LI-KW1