Position Overview: The Economic Research & Policy Department (ERP) conducts industry and economic research, performs fiscal and economic impact modeling, and analyzes NYCEDC projects to inform key policy and investment decisions. The team tracks economic trends and provides insights to City Hall, policymakers, and the public, while also developing tools to evaluate, measure, and report on project outcomes. ERP advances high-impact thought leadership on inclusive and innovation-driven economic development. 

The Assistant Vice President will bring advanced expertise in econometrics and data science to ERP, strengthening the department’s ability to evaluate public policies, model economic outcomes, and develop rigorous, reproducible analytical tools. This person will lead the design, implementation, and maintenance of sophisticated econometric and quantitative models. Their work will assess how proposed policies, programs, and investments could affect households, businesses, labor markets, government revenues, and New York City’s broader economy. 

The Assistant Vice President will apply econometric methods, causal inference, microsimulation, forecasting, and scenario analysis to complex economic and policy questions. They will establish strong modeling and validation practices, review technical work produced across the team, and help other researchers build their quantitative skills. The role requires deep technical expertise as well as the judgment and communication skills needed to translate complex methods and findings into clear, policy-relevant insights for decision-makers. 

Essential Duties & Responsibilities:

• Develop and maintain econometric, microsimulation, forecasting, and scenario-analysis models to evaluate the economic, fiscal, and distributional effects of City policies, programs, investments, and changing economic conditions.  
• Design empirical analyses using causal inference, quasi-experimental methods, and statistical modeling to assess policy effectiveness and estimate economic outcomes.  
• Build models that estimate behavioral responses to policy changes, including labor-market effects, price pass-through, demand elasticities, and household or business decision-making.  
• Evaluate model assumptions, validate results, conduct sensitivity and robustness analyses, and clearly communicate uncertainty and methodological limitations.  
• Use R to create reproducible analytical workflows, automate processes, and manage large or complex datasets.  
• Lead technically complex research projects from initial scoping through modeling, validation, and delivery, coordinating with internal teams, City agencies, external researchers, and consultants.  
• Collaborate with economists, policy researchers, and cross-functional teams to frame research questions, select appropriate methods, and incorporate evidence into policy and investment decisions.  
• Translate complex findings into clear, policy-relevant reports, briefs, presentations, data visualizations, and recommendations for technical and nontechnical audiences.  
• Train and mentor ERP staff, contribute to department research strategy, and respond to high-priority analytical requests from agency leadership, partner agencies, and City Hall.  
• Other duties as assigned.  

Requirements:

• Master’s degree in Economics, Statistics, Data Science, Public Policy, Applied Mathematics, Computer Science, or a related quantitative field required.  
• 5+ years of relevant experience in applied economic research, econometric analysis, statistical modeling, data science, policy evaluation, or related quantitative work.  
• Advanced proficiency in R, including the ability to write complex, reproducible, and well-documented analytical code from scratch. Familiarity with similar languages like Python will also be considered.  
• Experience applying econometric and statistical methods in a professional setting, including causal inference and quasi-experimental approaches such as difference-in-differences, instrumental variables, event studies, regression discontinuity, panel-data methods, or synthetic controls. 
• Experience developing microsimulation, forecasting, behavioral, policy-simulation, scenario-analysis, fiscal, or economic-impact models, with a strong understanding of model specification, identification, uncertainty, sensitivity testing, and validation. Strong preference will be given to candidates with demonstrated experience in a professional setting. 
• Demonstrated experience working with large, complex, or linked datasets, including administrative records, longitudinal data, survey microdata, or geospatial data.  
• Experience with public economic and demographic data sources, such as American Community Survey (ACS) Public Use Microdata Sample (PUMS), Current Population Survey (CPS), Quarterly Census of Employment and Wages (QCEW), and other comparable sources, is strongly preferred. Experience with complex survey methods is a plus.  
• Demonstrated written, verbal, and visual communication skills, including the ability to explain complex concepts and findings to technical and nontechnical audiences.  
• Experience leading complex projects, managing competing priorities, and exercising sound methodological judgement 
• Ability to collaborate effectively with researchers, program teams, agency leadership, external partners, and other stakeholders. 
• New York City residency is required within 180 days of hire.