Assistant Vice President, Advanced Data Analytics

nycedc; New York (NY); On-site; USD 150,000 - 210,000; Full time

Job summary

NYCEDC seeks an Assistant Vice President to lead econometric and data science work in the Economic Research & Policy Department. You will design and maintain sophisticated models, assess policy impacts on households, firms, and city revenues, and translate findings into actionable policy insights.

You will mentor staff, establish rigorous validation practices, and collaborate with economists and cross-functional teams to support decision-making for City policies and investments.

Qualifications

• Master's degree in Economics, Statistics, Data Science, Public Policy, Applied Mathematics, Computer Science, or related field.
• 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 writing complex, reproducible analytical code; familiarity with Python considered.
• Experience with econometric methods in professional settings, including causal inference and quasi-experimental approaches.

Responsibilities

• Develop and maintain econometric, microsimulation, forecasting, and scenario-analysis models to evaluate the effects of City policies and investments.
• Design empirical analyses using causal inference and quasi-experimental methods to assess policy effectiveness.
• Build models capturing behavioral responses to policy changes, including labor-market effects and household decisions.
• Evaluate model assumptions, validate results, and communicate uncertainty clearly.
• Use R to create reproducible analytical workflows and manage large datasets.
• Lead technically complex research projects from scoping to delivery, coordinating with internal teams and external partners.
• Collaborate with economists and policy researchers to frame questions and translate findings for decision-makers.
• Translate findings into policy-relevant reports, briefs, and visualizations.
• Train and mentor ERP staff and respond to high-priority analytical requests.
• Other duties as assigned.

Skills

Econometrics

Data Science

Causal Inference

Forecasting

Policy Evaluation

Leadership

Education

Master's degree in Economics or related quantitative field

Tools

R

Python

Job description

Our Vision : To make New York City the global model for inclusive innovation and economic growth, fueled by the City's diverse people and businesses.

Our Mission : Creating a vibrant, inclusive, and globally competitive economy for all New Yorkers.

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 (P