Team and expertise

Overview

The current planning lead can set the technical and product direction, but that is not, by itself, a sufficient team for full implementation. A credible plan distinguishes between:

  • the current project lead
  • the external review capacity the project needs
  • the implementation expertise required to execute the roadmap

This chapter describes the kinds of roles and expertise the project needs, not headcounts or compensation.

Current project lead

Max Ghenis

Max Ghenis leads PolicyEngine and brings the core infrastructure experience behind the Enhanced CPS and PolicyEngine’s tax-benefit models. His role in this project is architectural leadership, product direction, and integration with the broader PolicyEngine ecosystem.

Needed review capacity

The public proposal should not imply named advisors, reviewers, or staff are committed unless those commitments are explicit. Before full implementation, the project should recruit review capacity covering:

  • Social Security policy and benefit-rule expertise
  • retirement economics and wealth measurement
  • dynamic microsimulation practice
  • statistical imputation, calibration, and validation
  • public-interest product and user research

Required expertise

The project should cover at least the following kinds of expertise during implementation:

Technical lead or research engineer

Implementation leadership is needed to own the longitudinal populace pipeline, modeling infrastructure, and reproducibility workflow. This capacity should not be treated as optional.

Research economist or quantitative social scientist

This expertise is needed for validation design, policy interpretation, benchmark replication, and reform analysis. The project needs people whose job is to ask whether the results are economically credible, not just whether the code runs.

Data engineering and data science

The project requires substantial work on harmonization, ingestion, versioning, and reproducibility across the surveys and administrative sources that populace integrates and calibrates against. This is a real workload, not a background task.

Research assistance

Research assistance will likely be needed for:

  • documentation of policy rules
  • benchmark assembly
  • literature synthesis
  • validation-table construction

Review and governance

The project should use structured outside review rather than relying only on internal confidence. That review should include:

  • Social Security policy experts
  • microsimulation practitioners
  • survey and wealth experts
  • users from outside the immediate project team

The goal is to catch overclaiming early and document disagreements openly.

Operating model

The recommended operating model is:

  • the project lead sets scope, standards, and go/no-go decisions
  • external reviewers inform validation standards and policy relevance
  • the implementation team owns delivery
  • reviewers challenge the validation record at each major gate

That is a healthier structure than informal part-time execution by a small core team.

Why this matters

This project is easy to underscope because it looks like an extension of existing PolicyEngine work. It is not just that. Dynamic microsimulation adds persistent complexity in data construction, transition modeling, validation, and product boundaries. The team section should therefore signal seriousness about staffing from the outset.