NERA Consultant (New York City)

Marsh McLennan•New York, NY

4d•$138,000 - $235,000•Hybrid

About The Position

National Economic Research Associates, Inc. is seeking candidates for the following full-time positions based in the New York, NY office (A hybrid work schedule may be permitted within a commutable distance from the worksite, in accordance with company policies.) Consultant: (Multiple Positions) We will count on you to: Conduct economic research and analysis to evaluate the competitive effects of mergers and acquisitions, as well as litigation and consumer harm issues. Develop economic models to explain the competitive dynamics of firms and industries. Apply efficient computational techniques and AI to query and analyze large-scale structured and unstructured data. Leverage the same tools to design and create exhibits, including charts, tables, and maps, which demonstrate economic results. Manage projects, including planning, prioritizing workstreams, supervising consulting staff’s work to ensure adherence to methodological guidelines, project goals and deadlines, and coordinating with senior staff. Communicate with clients and counsel, including responding to inquiries and requests, advising on project deliverables, and presenting economic analysis outcomes. Draft sections of economic white papers, letters, and expert reports in litigation, to present the results of economic and econometric analyses. Prepare analyses and presentations for engagement with relevant antitrust agencies, including the U.S. Federal Trade Commission (FTC) and the Department of Justice (DOJ). Direct the evaluation of AI integration into workflows and analyst teams’ implementation of AI capabilities in economic research and analysis. Apply knowledge of economic analysis processes and tools to identify strategic areas of reinvention using AI capabilities to reduce costs and increase capabilities, including deployment of machine learning-based econometric and simulation methods. This position has no dedicated full-time direct reports but will plan, direct and supervise the work performed by approximately 2-10 consulting staff on a project-by-project basis.

Requirements

Must have a Bachelor’s degree or foreign equivalent in Economics or a related field plus five (5) years of experience in the position offered or a related position.
Alternatively, Employer will accept a Master’s degree or foreign equivalent in Economics or a related field plus three (3) years of experience in the position offered or a related position.
Must have five (5) years (or three [3] years with a Master’s) of experience with all of the following: Programming in Python and Stata on raw data, ranging from small to large, to prepare data analyses and visualizations that demonstrate economic arguments in horizontal and vertical mergers; Econometrically evaluating unilateral and non-unilateral effects from a potential merger, testing market definitions and calculating price elasticities, by applying appropriate econometric and statistical theory and techniques in hypothesis testing, parameter estimation, parameter identification, and model selection; Formulating data requests, and describing the data inputs, methodologies, and assumptions for preparing economic analyses that address antitrust questions specific to different industries; Deriving insights related to market structure, competition, firm pricing, and costing behavior from Enterprise Resource Planning (ERP) databases, namely Oracle or SAP, and from Customer Relationship Management (CRM) data systems, namely Salesforce, to respond to information requests from antitrust regulatory agencies or to inform economic advocacy work in antitrust merger cases; Verifying researchers’ and analysts’ execution of data analysis in Python, Stata, and Excel to ensure results are replicable across data analysis tools or withstand scrutiny in antitrust merger reviews or in litigation cases; Preparing raw data, underlying Python and Stata code, and analysis exhibits in compliance with data submission guidelines from antitrust regulatory agencies for analysis backup, or in response to Second Requests and to Voluntary Access Letters; Developing qualitative economic evidence from economic literature, financial documents, business strategic plans, press reports, industry publications, SEC filings, or legal documentation; Applying frameworks and tools from Merger Guidelines, including the Herfindahl-Hirschman Index (HHI), Hypothetical Monopolist Test, Gross Upward Pricing Pressure Index (GUPPI), and Diversion Ratios to address theories of harm in mergers and acquisitions.

Responsibilities

Conduct economic research and analysis to evaluate the competitive effects of mergers and acquisitions, as well as litigation and consumer harm issues.
Develop economic models to explain the competitive dynamics of firms and industries.
Apply efficient computational techniques and AI to query and analyze large-scale structured and unstructured data.
Leverage the same tools to design and create exhibits, including charts, tables, and maps, which demonstrate economic results.
Manage projects, including planning, prioritizing workstreams, supervising consulting staff’s work to ensure adherence to methodological guidelines, project goals and deadlines, and coordinating with senior staff.
Communicate with clients and counsel, including responding to inquiries and requests, advising on project deliverables, and presenting economic analysis outcomes.
Draft sections of economic white papers, letters, and expert reports in litigation, to present the results of economic and econometric analyses.
Prepare analyses and presentations for engagement with relevant antitrust agencies, including the U.S. Federal Trade Commission (FTC) and the Department of Justice (DOJ).
Direct the evaluation of AI integration into workflows and analyst teams’ implementation of AI capabilities in economic research and analysis.
Apply knowledge of economic analysis processes and tools to identify strategic areas of reinvention using AI capabilities to reduce costs and increase capabilities, including deployment of machine learning-based econometric and simulation methods.