Data Analytics
I'm actively transitioning into data analytics, building on a foundation in UX and technical writing. The same instincts that make documentation clear: understanding structure, anticipating the reader, and communicating findings precisely, translate directly into analytics work. This page will grow as new projects complete.
IBM Data Analyst Professional Certificate
An 11-course professional certificate covering the full analytics workflow: data collection, wrangling, SQL, Excel, Python, visualization, and storytelling with data. Two capstone projects anchor the certification with real deliverables.
Completed Projects
Two finished projects from the IBM Data Analyst Professional Certificate, each expanded well beyond the original course scope into standalone portfolio pieces.
End-to-End Stock Market Analytics Pipeline
Python · yfinance · Pandas · Plotly · Web Scraping
Acting as a data analyst for a startup investment firm, helping clients make informed decisions about stock investments.
Started as an IBM guided notebook covering basic price and revenue charts for two stocks. Rebuilt into a fully automated, config-driven pipeline: extract historical prices via yfinance and quarterly revenue via web scraping, validate and structure the data, compute five financial metrics, and generate nine interactive Plotly visualizations across five tickers and an S&P 500 benchmark.
A modular notebook where changing the ticker list or date range in a single config dictionary regenerates every chart, metric, and written insight automatically. Outputs include nine standalone HTML dashboards, CSV exports, and an auto-generated insights file.
Tesla led total return at roughly +1,878% over the period, about 10x the S&P 500. Apple posted the strongest risk-adjusted performance with a Sharpe Ratio of 1.01. GameStop's correlation with the other stocks stayed near zero, reflecting retail-driven price action disconnected from broader market trends.
- yfinance price & volume extraction
- BeautifulSoup revenue scraping
- 5 financial metrics (Sharpe, CAGR, drawdown, etc.)
- 9 interactive Plotly dashboards
- Automated insight generation
- CSV / HTML export pipeline
Developer Ecosystem Analysis 2024
Python · SQL · Excel · IBM Cognos · Stack Overflow Survey · ETL
Data analyst at a global IT and business consulting firm, producing a technology trend report for hiring managers, technical leaders, and workforce planners.
Combined three IBM capstone data collection methods, REST API job posting data, web-scraped salary data, and the 2024 Stack Overflow Developer Survey, into a single end-to-end notebook. Cleaned and validated all sources, then analyzed current versus future technology demand across programming languages, databases, cloud platforms, and web frameworks.
A consolidated analysis notebook, dashboard-ready CSV exports, a three-tab IBM Cognos dashboard (current usage, future trends, demographics), and an executive-style presentation with business recommendations.
TypeScript, PostgreSQL, and AWS rank highly in both current and desired usage, marking them as baseline industry expectations. Go, Rust, FastAPI, Next.js, and Cloudflare show the strongest future growth signals, while jQuery, PHP, Oracle, and Heroku show declining future interest.
- Jobs API (employer demand)
- Web-scraped salary data
- 2024 Stack Overflow Developer Survey
- Current technology usage
- Future technology trends
- Developer demographics
Upcoming Projects
Projects I'm scoping now. Details and deliverables will be added as they take shape.
Mobile Game Analytics
Co-developing a mobile game with my brother. Planning to instrument player behavior, track session data, and analyze engagement and retention patterns as the game develops.
UX & Product Analytics
Applying analytics to UX research questions. Bridging my documentation and design background with data-driven product insights.
Why Analytics
My background in UX and technical writing is more of a head start than a detour. Good documentation requires understanding a system deeply, identifying what matters, and communicating it without noise. Good analytics work requires the same thing. The tools are different. The thinking is not. My Computer Graphics Technology degree gave me a foundation in structured thinking and systems design that maps directly to how I approach data problems now.