Sheet 01 · Overview Austin · remote

Applied ML for workforce strategy.

MLOps and neural networks for people analytics — built so leadership can make workforce decisions backed by real data, not gut feel.

Applied Machine Learning Engineer focused on people analytics and workforce strategy. People Research Scientist at Meta. M.S. I-O (SJSU), B.S. Psychology (CofC). Agents since Nov '22; neural nets on comp and attrition at Aon before that. Some consulting on the side.

Practice

Usually three teams: I-O writes the rubric, data science trains the model, MLOps ships and monitors it in production. I do all three, which matters when the work has to hang together.

  1. Pre-2022Neural nets for job classification, attrition, pay equity — Aon, then Meta
  2. Nov '22 →Agent pipelines for job analysis and people research
  3. NowContract work: psychometrics, MLOps pipelines, agent orchestration for people analytics and workforce strategy teams

Services

Fixed scope. Running code and documentation, not a strategy deck.

SVC · 01

Measurement & job architecture

SIOP job analysis, competency models, leveling — the spec your models should follow.

Taxonomies · rubrics · automation-readiness scores · HRBP/legal docs

SVC · 02

Skills & inference

Ontology design, validation protocols, match-rate benchmarks.

Validation studies · governance rules · mobility integrations

SVC · 03

Agent pipelines

Multi-step workflows for people research — taxonomies, evidence, eval loops. In production since Nov '22.

Agent specs · eval harnesses · human review gates · tool contracts

SVC · 04

Neural nets & MLOps

Neural nets or classical ML, shipped and monitored in production — training pipelines, Python/SQL backends, React/Next if analysts need a UI.

Models · training pipelines · monitoring · analyst UIs · PyTorch / Spark

Engagements

Scope

Problem, stakeholders, data on hand, what done means for legal and the business.

Diagnostic

Read what you have, talk to users, write up gaps. Fixed fee.

Build

Weekly checkpoints. Methods written down.

Handoff

Artifacts, replication notes, walkthrough with your team.

Track record

From full-time roles building people analytics and workforce strategy systems. Same work I take on contract.

Nov '22

Agent systems for people research

1,227

Roles in job architecture platform

96%

Skills inference match rate

200+

Research workflows

People Research Scientist · Meta

  • Job analysis platform — multi-agent pipeline across 1,227 roles (task taxonomies, competencies, automation-readiness)
  • Skills intelligence — 70k employees × 20k skills, 96% match
  • AI Adoption Index — CFA + bootstrap replication, 526 business units
  • React/Next tooling for ~50 analysts; 200+ workflows

Earlier · Aon, GPTW

2014 — 2020
  • Aon — neural nets on a global comp database; attrition, pay equity, high-performer models
  • Great Place To Work — Fortune 100 Best Companies assessments

Education

M.S., I-O Psychology — San Jose State University 2015
B.S., Psychology — College of Charleston 2012

Stack

People analytics Workforce strategy MLOps Neural networks Multi-agent systems SIOP job analysis IRT / CFA / EFA Skills ontologies PyTorch Python SQL React / Next.js Spark

Lab

Public GitHub. Side projects and prototypes. Mobile-first, zero tracking, era-honest.

Contact

Describe the problem — people analytics, workforce strategy, MLOps, or model-building — and I'll tell you if it's a fit.

Select projects · NDA ok · Austin or remote

jcdavis131@gmail.com