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dez-data/README.md

Samuel Agondeze Kisoke

Data Science/Analytics · Business Intelligence · MEL Practitioner

I turn fragmented, multi-source datasets into evidence that policymakers, program leads, and business owners actually act on. My work spans agricultural economics in Ghana, public health monitoring in rural Uganda, and SME tooling built for entrepreneurs who can't afford enterprise software.

BSc Statistics (Data Science Track), Kwame Nkrumah University of Science and Technology, Ghana, 2025. Mastercard Foundation Scholar, Cohort 8.


What I'm building toward

Data engineering, business intelligence, and development-sector analytics roles. I'm strongest where statistical rigor meets stakeholder communication, the kind of work where a correlation coefficient has to become a one-page recommendation a government administrator will actually use.


Featured Projects

Consolidated five unlinked datasets spanning 63 years (1961-2023) from FAOStat, the Ghana Statistical Service, and World Bank sources. Built three live Power BI dashboards and ran correlation and regression analysis in Python to surface a structural constraint in cocoa export growth: area harvested correlates at r=0.16 with time, against r>0.85 for every food crop in the dataset. Delivered formal recommendations to Amalitech supervisors. Built with Abigail Afful.

Python pandas scipy statsmodels Power BI DAX

Compared ARIMA, ETS, and Prophet on 63 years of World Bank GDP data for Ghana. Prophet beat ARIMA by 27% and ETS by 37% on RMSE, largely because it handled structural breaks like the 1983 economic crisis better than the alternatives. Full stationarity testing, ACF/PACF analysis, and Ljung-Box residual diagnostics documented in R Markdown.

R forecast prophet tseries R Markdown

Built a free Excel-based inventory and profit-tracking system for market vendors and micro-enterprises that can't justify the cost of accounting software. Multi-sheet relational structure with SUMIF and VLOOKUP automation, a live Google Sheets demo, and a PDF user guide written for non-technical operators.

Excel SUMIF VLOOKUP Data Validation


Technical Toolkit

Analysis: R · Python (pandas, numpy, scipy, statsmodels) · STATA · SPSS · SQL (PostgreSQL) Visualization: Power BI (DAX, data modeling, published dashboards) · Excel Data Collection: Kobo Toolbox · ODK · CommCare · Google Forms MEL: Logframe construction, results frameworks, indicator design, feedback and accountability systems


Background

Field-level data collection across 23 rural communities in Mubende District, Uganda drove reporting completeness from 71% to 92% within three months at BRAC Uganda, by separating systematic collection failures from entry errors instead of treating every gap in the data the same way. That distinction, between a broken process and a one-off mistake, still shapes how I approach any dataset with quality issues.


Credentials

IBM Data Fundamentals · AWS Educate Machine Learning Foundations · Generative AI with AWS (Udacity) · DataCamp Data Literacy Certification · MEL Certificate, Philanthropy University


Get in Touch

📧 samuelasteragondeze@gmail.com 💼 linkedin.com/in/samuel-agondeze-kisoke

Pinned Loading

  1. sub-saharan-soil-analysis sub-saharan-soil-analysis Public

    Soil chemistry analysis and crop recommendation logic across sub-Saharan Africa using the iSDA dataset

    Jupyter Notebook

  2. ghana-agriculture-analysis ghana-agriculture-analysis Public

    Power BI dashboards and Python statistical analysis of Ghana's agricultural sector, demonstrating data visualization, correlation and regression modelling, and policy research skills developed duri…

    Jupyter Notebook