Data Scientist & Analytics
Data Scientist & Decision Intelligence Engineer · B.S. Business Analytics & Information Systems, University of Iowa · Iowa City, IA
I'm John Kirima, a data analyst and applied data scientist focused on turning messy information into clear, useful decisions. I build decision systems that combine forecasting, optimization, and machine learning to turn uncertainty into margin for businesses that can't afford to guess.
More about me→Built end-to-end as a full case study with production-ready artifacts (model, feature list, imputer, and scoring functions). Each project below turned messy, ambiguous data into decisions that moved the numbers, from recovered revenue to optimized operations.
View Case Study ↗
View Case Study ↗
View Case Study ↗
$ dataforge run --pipeline full [Agent 1] → Data cleaning complete (14 columns standardized) [Agent 2] → Outlier detection flagged 47 anomalies [Agent 9] → Executive summary generated
I'm John Kirima, a data analyst and applied data scientist focused on turning messy information into clear, useful decisions.
My work sits at the intersection of analytics, machine learning, and systems thinking. I like projects that go beyond surface-level reporting and push toward explanation, structure, and business meaning.
Python, SQL, Oracle APEX, HTML/CSS
Power BI, Microsoft Excel, ETL Processes, Data Cleaning
Machine Learning, Statistical Analysis, SHAP Interpretability, LLM Integration, Multi-Agent Systems, NLP, BERTopic, VADER, Sentiment Analysis
Demand Forecasting, Inventory Allocation, Optimization Under Uncertainty, Scenario Modeling
Data Analyst Intern
Iowa City, IA
Feb 2025 – Jun 2025
Operations leaders lacked timely, trustworthy visibility into incident and operational data. Reporting was manual and scattered across SharePoint lists, too slow and too fragmented to support confident day-to-day decisions.
I built an automated analytics pipeline that fed interactive Power BI dashboards. Data flowed directly from SharePoint into Power BI, while stakeholder interviews shaped which metrics, filters, and views actually mattered to the people making operational calls.
Power Query transformed raw, inconsistent records into clean, reliable reporting tables, replacing manual spreadsheet work with a repeatable, refreshable system. The finished dashboards gave teams real operational visibility and turned reactive guesswork into faster, evidence-based decisions.
Open to collaborations in analytics, product, ML, or decision intelligence.
