Work
Four projects, each led by what it found. Every case study links to the source.
Reaching level 9 in ranked TFT meant a top‑4 finish 87% of the time.
I loaded 399,906 ranked boards into Snowflake to see what separates top‑4 finishes.
TFT Ranked Match Analysis in Snowflake, Fall 2025. Snowflake, SQL, VARIANT / FLATTEN, Power BI, Data Cleaning
Top-4 rate by player level Name Top-4 rate Level 7 26.9%Level 8 51.3%Level 9 86.6%Half of all boards finish top four Source: 399,906 boards from 49,977 ranked matches, queried in Snowflake.
Electronics was losing margin to discounts and returns.
A PostgreSQL star schema and Power BI dashboard over 63,635 order items found 7.62% average discounting and a 7.26% return rate in Electronics.
Northstar Commerce Executive BI Dashboard & Data Pipeline, 1 Month. PostgreSQL, SQL, Power BI, DAX, Data Modeling
Return rate by product group Name Return rate Electronics7.62% average discount 7.26%Accessories44.21% gross margin 5.55%Source: 63,635 order items, $5.94M net revenue, modeled in PostgreSQL.
Only 22 of 163 NFL players earned an elite fantasy tier.
I scored players on Value Over Replacement so every position shares one scale, then used K-Means to split them into four draft tiers: 22 elite, 36 high-end starters, 73 average, 32 below replacement.
NFL Player Clustering & Fantasy Tier Analytics, Spring 2025. Python, Scikit-Learn, K-Means, Pandas, Value Over Replacement (VOR)
Players per fantasy draft tier Name Players Elite 22High-end starters 36Average 73Below replacement 32Source: 163 players in the repo's 2024 sample dataset, K-Means with k=4 on Value Over Replacement.
Scrum Master for a six-person team that shipped a client’s site redesign.
Ran sprints in Jira, handled client communication, and led a usability audit of the service pages for Woodland Country Manor.
Woodland Manor Agile Web Redesign & Systems Overhaul, Jan to May 2026. Agile / Scrum, Jira, Wix Studio, Backlog Prioritization, User Stories
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