AVP, Advanced Data Analytics — Policy Impact & Modeling Lead

New York City Economic Development Corporation; New York (NY); On-site; USD 105,000 - 108,000; Full time

Benefits offered by this job

Medical, dental, and pharmacy plans

Vision and hearing benefits

Flexible spending accounts

Disability coverage

Life insurance

Up to 25 vacation days

Floating Holidays and Summer Fridays

Parental leave - up to 20 paid weeks

Retirement programs (401a, 457b)

Tuition Reimbursement

Job summary

New York City Economic Development Corporation seeks an Assistant Vice President of Advanced Data Analytics to lead econometric modeling and quantitative policy analysis within the Economic Research & Policy Department. You will design and implement advanced models, conduct rigorous validation, and translate findings into policy recommendations for City Hall and partners.

The role requires deep technical expertise in econometrics, large-scale data handling, and leadership to guide

Qualifications

• Master’s degree in Economics, Statistics, Data Science, Public Policy, Applied Mathematics, Computer Science, or a related quantitative field is 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; Python familiarity considered.
• Experience with econometric and statistical methods including causal inference and quasi-experimental approaches.
• Experience developing microsimulation, forecasting, behavioral, policy-simulation, or economic-impact models with validation.
• Experience working with large, complex datasets and public economic data sources is preferred.
• New York City residency is required within 180 days of hire.

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.

Skills

Econometrics

Data Science

Causal Inference

Statistical Modeling

Policy Evaluation

Leadership

Education

Master's degree in Economics or related quantitative field

Tools

R

Python

Job description

New York City Economic Development Corporation seeks an Assistant Vice President of Advanced Data Analytics to lead econometric modeling and quantitative policy analysis within the Economic Research & Policy Department. You will design and implement advanced models, conduct rigorous validation, and translate findings into policy recommendations for City Hall and partners.

The role requires deep technical expertise in econometrics, large-scale data handling, and leadership to guide