I build FTE models, inflow forecasts and automated data pipelines that turn ad-hoc workforce planning into repeatable, data-driven decisions, using Python, SQL, Power BI, Snowflake and dbt.

Jesse O'Brien, Workforce Modelling & Data Specialist based in Auckland, New Zealand

Auckland, New Zealand · remote friendly

4+ years in workforce analytics

PL-300 certified

Python · SQL · Power BI · Snowflake · dbt

Who is Jesse O'Brien?

A little bit about me.

I'm a data specialist with over four years working across workforce modelling, forecasting, reporting, and automation inside ACC, New Zealand's national injury insurer, building FTE models, inflow forecasts, 50+ Power BI dashboards, and automated pipelines that replaced manual processes end-to-end. My toolkit spans Python, SQL, dbt, Snowflake and Power BI.

I'm equally comfortable as a hands-on technical practitioner and as the data SME in the room, translating complex data work into decisions that stakeholders can act on, from planners and real-time analysts through to executive leadership.

Outside of my day-to-day role, I'm still building new tools, forecasting techniques, and side projects, a few of which are below. I also write about what I'm learning on the Blog.

What I'm Building.

Selected projects.

NYC 311 Demand Intelligence

An end-to-end data platform forecasting NYC 311 service request demand across 6.2M records and 14 complaint categories. A production-style dbt + DuckDB pipeline feeds a hybrid Prophet/LightGBM forecasting model (27.6% mean MAPE) and a Gemini-powered natural language data assistant, all served through a Streamlit dashboard with live staffing recommendations.

PythondbtDuckDBProphetLightGBMStreamlitGemini API

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Elsewhere: A Global Lifestyle & Cost Dashboard

An interactive Tableau dashboard that helps you find where your salary goes furthest based on what matters most to you. A Python pipeline combines data from five sources across 618 cities to power an interactive world map, personalised rankings, city comparisons, and a supporting data story.

PythonBeautifulSouppandasgeopyTableau

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Aegis Run

A full-stack fantasy draft game built on a game-agnostic simulation engine: draft a roster, then simulate a group stage and bracket run against a team-strength and synergy model built from scratch. Includes a deterministic (hash-seeded, not random) daily challenge with four independently-varying rulesets, and a Postgres/Drizzle data layer seeded from a CSV pipeline, deployed on Vercel from an npm-workspace monorepo.

Next.jsTypeScriptPostgresDrizzle ORMVercel

View project

View all projects

My experience.

Workforce Modeller

Current

Apr 2026 – Present

  • Act as a key modelling and data SME within a WFM function of 70+ staff, advising planners, real-time analysts, and leadership on technical feasibility, data interpretation, and process capability.
  • Build FTE scenario models for new business initiatives, quantifying workforce impact of moving work between teams, standing up new functions, or absorbing inflow changes at scale.
  • Develop what-if and transition models mapping how changes in one area of the business propagate FTE requirements across the wider organisation.
  • Led the end-to-end data modelling and allocation framework design for new workforce functions, from initial scoping through to operationalisation and steady state.

Reporting Analyst

Jul 2025 – Apr 2026

  • Designed, developed and maintained 50+ Power BI dashboards, Streamlit applications, and Excel reports supporting WFM operations, planning, and performance reporting up to executive level.
  • Extracted, cleaned and modelled workforce data from Snowflake, Salesforce, and SQL sources using Python and dbt, ensuring accuracy and timely delivery across WFM reporting cycles.
  • Advised reporting analysts across WFM on data interpretation, query design, and what is achievable within ACC infrastructure constraints.

Workforce Planner

Jul 2024 – Jul 2025

  • Built volume forecasting models using Prophet and LightGBM to predict incoming work inflow across departments, providing the demand signal foundation for FTE planning and capacity modelling.
  • Designed and built WFM forecasting pipelines and department-level inflow models from the ground up, replacing ad-hoc manual processes with automated, reproducible workflows in dbt, Snowflake, and Python.

Earlier at ACC

Operations Analyst

Aug 2023 – Jun 2024

  • Built Python automation scripts that eliminated manual stakeholder processes and directly reduced the need for unplanned overtime, delivering measurable cost avoidance for the business.

WFM Real Time Analyst

May 2022 – Aug 2023

  • Monitored real-time workforce activity across multiple business units within a 250+ FTE operation, managing intraday staffing decisions to maintain service levels.

What I Work With.

My skills & credentials.

Workforce Modelling

FTE modelling Capacity planning Scenario analysis Inflow forecasting Transition modelling Allocation design

Languages

Python pandas Prophet LightGBM scikit-learn SQL DAX M / Power Query VBA Jinja

Data Platform

Snowflake dbt GitHub Actions Azure Pipelines Git

Visualisation

Power BI (PL-300) Streamlit Excel PowerPoint

Automation

Python scripting Power Automate Selenium

Tools

Genesys Cloud Salesforce CRM Emite Microsoft 365

Certifications

Power BI Data Analyst Associate (PL-300)

Microsoft

2023

IBM Data Analyst Professional Certificate

IBM / Coursera

2025

Google Data Analytics Professional Certificate

Google / Coursera

2022

Google Project Management Professional Certificate

Google / Coursera

2025

Lean Six Sigma: White Belt

2024

Education

Bachelor of Business Administration, Project Management & Information Systems

University of Maine at Presque Isle

Let's connect.

Always happy to talk data, modelling, or forecasting. Drop me a line.

[email protected]
Auckland, New Zealand
Resume

© 2026 Jesse O'Brien.