Columbus, Ohio · Data science and analytics
I’m Ekow Yalley, a University of Michigan graduate with a B.S. double major in Data Science (Econometrics) and Biology. I build models, reporting pipelines, validation systems, and operational data workflows with Python, SQL, and AWS.
Experience
Operations Data Analyst
Build weather-data workflows for tapping decisions, equipment-monitoring systems for maintenance alerts, and a centralized SQL/ETL architecture connecting factory, inventory, purchasing, and shipping records.
Test Bench Operator - Data & Automation [Contractor]
Programmed and adjusted drive-test scripts, investigated anomalies in test data, and coordinated with technicians and engineers to keep component tests running and accurately reported.
Data Lead [Contractor]
Structured comparisons across rail cars, operating conditions, and track segments; used Python and Orange to surface recurring differences and turn them into visual material for technical team discussions.
Founder
Founded and continue to lead a 501(c)(3) nonprofit that pairs college volunteers with K–12 students for free tutoring and mentorship through a volunteer-led service model.
Selected work
Each project shows the question, approach, result, and checks behind the work.
Built a leakage-safe logistic-regression baseline using 49,999 validated public NYC 311 records and a target derived from actual creation and closure timestamps.
Result: the model materially outperformed the 59.5% majority-class benchmark. The one limitation is that production use would require time-based validation and drift monitoring.
Built a reproducible Python pipeline that validates sales and customer files, joins them, aggregates regional/category reporting, and reconciles $7,816.00 from source to output.
Result: eight pipeline checks and four unit tests pass, with revenue reconciling exactly from source to final output. The current sample contains 48 transactions.
As Data Lead, organized months of train-run data into car-, condition-, and segment-level comparisons, surfaced recurring differences in rail-car behavior, and built comparative visual material for technical discussions about maintenance and safety priorities.
Private-data note: the underlying rail dataset and code cannot be published.
Built for fun
Smaller builds that show curiosity and range without competing with the data-focused work above.
Python applicationRunnable locally
A two-player Snake adaptation built with Python Turtle, including separate controls, live scoring, body growth, and player-to-player collision logic.
Education
Double major: Data Science (Econometrics) and Biology
Contact
I’m exploring junior data analyst, BI, reporting, operations-analytics, data-quality, and data science opportunities.