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Kestrel Metric Lab

Statisticians performing NYC Local Law 144 bias audits and multi-state disparate-impact analyses for hiring tools.

New York, United States

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At a glance

Frameworks
  • NYC Local Law 144
  • Illinois HB 3773
  • Colorado AI Act (SB 24-205)
Services
Bias audit
Jurisdictions served
United States
Headquarters
New York, United States
Industries
HR tech
Firm size
2–10 people
Gap-analysis price band
Under $5k
Retainer price band
Undisclosed
Engagement models
Fixed-scope project
Remote / on-site
Remote only
Languages
English
Year founded
2023

About

Kestrel Metric Lab is a small New York group of four statisticians that carries out the independent bias audits required under New York City's Local Law 144 and prepares the equivalent disparate-impact analyses that employers in Illinois and Colorado are increasingly asked to produce. The lab's founder, Jonah Feldstein, completed a doctorate in statistics before working on hiring analytics at a payroll company; the other members are quantitative researchers who join per engagement. Each audit begins with a data template, a short call to confirm the categories in scope and a signed independence statement, and ends with a public summary and a longer technical memo for the client's counsel. For a single automated employment decision tool with clean historical data, fees stay under five thousand dollars and turnaround is roughly two weeks. Vendors with many customers using the same tool are quoted on a per-tool basis rather than per employer. Kestrel does not provide policy drafting, does not advise on whether a tool is legally in scope, and will not audit tools it helped design. The team works remotely across the Northeast and takes on no more than six audits at a time, so booking a slot two months ahead is usual during the spring reporting season.

Credentials

  • Not verified

    PhD Statistics

    Held by Jonah Feldstein

    PhD Statisticspublic profile cross-checked

✓ marks credentials we confirmed against the issuing registry or a reviewed certificate. Self-attested and public-profile credentials are shown for completeness but do not count toward verification. How we verify

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