Senior Data Analyst at Microsoft · Reno, NV
Greg Chedwick
Domain agnostic: I turn messy data into metrics, dashboards, and automation people actually use.
Senior analytics professional with 20+ years in data analytics and 6+ years leading analytics initiatives, spanning software licensing, mortgage and consumer lending, advertising, supply chain, and freight. I design scalable metrics, build dashboards that drive decisions, and automate the manual work that quietly eats teams alive — most recently with AI agents built in Copilot Studio. I do my best work in ambiguous 0-to-1 territory with minimal oversight.

By the numbers
Impact, quantified
Every figure below traces to a specific project in the career history — no round numbers without a story behind them.
4,300+
Hours automated per year
Anniversary and mid-term ordering workflows, enabling 3x business scaling in two years
$106M
On-time renewal lift
Driven by compliance analytics and automated deep-dive reporting
$3.2B
Agreement portfolio in view
Power BI dashboards giving stakeholders live visibility into portfolio health
$31M
Cost reduction
Data-driven business cases built with DMAIC and Agile methodologies
$5.7B
Revenue enabled
Process and system improvements substantiated through analytics
$60B+
Portfolio remediated
Loan modification campaigns supporting $25B+ in government programs
Career
23 years, three employers
Each bar spans one employer. Select a role to read what it involved — or read them all below, no clicking required.
Microsoft
Senior Data AnalystFusion Development, Operations Service Center
- Engineered scalable licensing data models, automated workflows, and developed Power Apps that automated anniversary and mid-term ordering — saving 4,300+ hours annually and enabling 3x business scaling over two years.
- Developed compliance analytics metrics and Power BI dashboards giving visibility into a $3.2B+ agreement portfolio, driving a $106M increase in on-time renewals.
- Designed agreement complexity models to identify bottlenecks, enabling targeted root-cause investigations and scalable automation for ad-hoc requests.
- Built custom AI automation with Copilot Studio to enable stakeholder self-service, integrate disparate data sources, and accelerate insight delivery.
Business Analytics SpecialistBusiness Process & Analytics, Commercial Ops
- Led global analytics backlog prioritization using Cost of Delay / Weighted Shortest Job First within a SAFe framework, ensuring timely deployment of high-impact BI across software licensing, advertising, and supply chain.
- Partnered with cross-functional stakeholders to define requirements and ship scalable dashboards that informed decisions and supported new program launches.
- Developed automated reporting pipelines and self-service tools across digital attach, hardware compliance, search, and advertising.
Business Operations AnalystProcess Management, Commercial Ops
- Crafted data-driven business cases using DMAIC and Agile methodologies, substantiating improvements that cut costs by $31M, reduced AR exposure by $400M, and enabled $5.7B in revenue.
- Engineered BI solutions and monitoring dashboards to track outcomes of process and system improvements.
Bank of America
Vice President, Consumer Products Strategic ManagerLoan Loss Mitigation and Portfolio Analytics
- Led the analytics team behind loan modification campaigns, remediating a $60B+ portfolio and supporting $25B+ in government programs through advanced BI and reporting.
Charles Schwab Bank
Finance Manager, Bank FinanceBank Finance
- Spearheaded development of the loan database and analytics infrastructure, improving reporting, lead generation, and portfolio management across Finance, Credit, and Compliance.
Toolkit
Skills, by years in the seat
Hover any tool in the ticker for what I've done with it. Below, bar length is hands-on years on one shared scale — two entries are marked as recent rather than deep, because being straight about that matters more than a longer bar.
Data & BI
- SQL15+ yrs
Complex querying, data modeling, large-scale analysis
- KQL5+ yrs
Kusto queries over log and telemetry data
- Power BI & DAX10+ yrs
Interactive dashboards, reporting, visualization
- SSMS & VS Code10+ yrs
Data modeling, analysis, AI-assisted coding with Claude Code and Copilot CLI
Data Engineering
- Microsoft Fabric & SSIS10+ yrs
ETL pipelines, SQL databases, lakehouses
- Azure DevOps10+ yrs
Plan, build, test, and deploy solutions
- Azure Platform Services5+ yrs
Function Apps, Logic Apps, Data Factory, serverless automation
- PythonGrowing
Data manipulation, scripting, automation
Automation & AI
- Power Automate & Power Apps7+ yrs
Workflow automation and self-service tools
- Microsoft Copilot StudioRecent
AI agents, low-code intelligent automation
Education
Master of Business Administration
University of Nevada, Reno · 2013
GPA 4.0 · Data Resource Management, Information & Communication Technology, Strategic Management
B.S. Business Administration
California State University, East Bay · 1998
Minor in Computer Science
Nights & weekends
Projects
Things I build outside work to stay sharp on the tools. Each one ships end to end — data in, decision out — rather than stopping at a notebook.
Netflix Ads Analytics
ShippedAn end-to-end analytics project simulating what an ad platform team needs to decide where ad inventory is worth buying — built as if for Netflix’s ad-supported tier.
- Cleaned and merged 32,000+ Netflix titles with 2025–26 global top-500 viewership data
- Designed a custom Ad Opportunity Score weighting hours viewed, sustained relevance, ratings, and recency
- Shipped an interactive Power BI dashboard alongside the notebook
- Python
- Pandas
- Matplotlib
- Jupyter
- Power BI
- Git
This Site
ShippedThe portfolio you’re reading. Built as a static site so the resume itself renders as live data visualization rather than a PDF nobody opens.
- Career history and impact metrics render from a single typed data file
- Charts validated for colorblind separation and contrast in both light and dark mode
- Deploys automatically to GitHub Pages on every push to main
- Astro
- TypeScript
- SVG
- GitHub Actions
Live project data
Netflix Ad Opportunity Score
Which titles are worth buying ad inventory against? I scored all 500 titles in the 2025–26 global top 500 by blending how much they were actually watched with how long they stayed relevant. These charts run on the real output of that analysis — not screenshots.
Top Titles by Opportunity Score
Score blends hours viewed, sustained ranking, rating, and recency.
Hover or focus a bar for the underlying numbers. A bar that fades at its end runs past the axis — the axis stops above the runner-up so the rest stay comparable.
How the Score Is Weighted
Hours viewed dominates deliberately — it is the closest available proxy for realised ad impressions. The rest adjust for staying power and quality.
- Total hours viewed75%Strongest predictor of ad inventory value
- Weeks in Top 1013%Measures sustained cultural relevance
- Vote average8%Higher-rated titles hold attention longer
- Release year4%Newer content attracts more viewers
Both charts respond to these.
Genres by Average Score
Averaged across every ranked title carrying that genre. Title counts vary — War is a small, high-performing set.
Data notes and known limits
Genre coverage is partial: only 21 of the top 60titles carry genre metadata, because most 2025–26 chart-toppers are newer than the catalogue they join against. That is why there is no genre filter on the titles chart — it would silently hide two-thirds of the data. The genre panel aggregates across all500 ranked titles, where coverage is high enough to average meaningfully.
KPop Demon Hunters is a genuine outlier at roughly four times the second-place score, which compresses everything below it. It is left in rather than trimmed, because the whole point of the metric is to surface exactly that kind of title.
Data generated 2026-07-26 from the project's processed output.
Get in touch
Open to analytics leadership roles
Based in Reno, NV, working remotely across time zones. If you are building something in the 0-to-1 space and need someone to make the data legible, I would like to hear about it.