KIGENYI SHIVAN VIOLET

Statistician | Data Scientist

Kampala, UG.

About

Highly analytical Statistician and Data Scientist with over 5 years of experience leveraging quantitative economics and advanced statistical methods to optimize inventory systems and drive business operational efficiencies. Expert in data collection, analysis, forecasting, and reporting using Python, R, SQL, and Excel, consistently translating complex data into actionable insights for strategic decision-making.

Work

Agroways (U) LTD

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Assistant Inventory Manager (Data Analyst)

Kampala, Central Region, Uganda

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Summary

Managed inventory and sales data analysis, reporting, and dashboard development to optimize procurement decisions and enhance operational efficiency for a leading agricultural company.

Highlights

Analyzed extensive inventory and sales data, applying statistical methods to inform precise procurement decisions and optimize warehouse operations, enhancing overall efficiency and reducing potential stock discrepancies.

Produced and presented regular statistical reports to senior management using Excel and ERP systems, significantly improving stock accuracy and enabling data-driven strategic decisions.

Designed and maintained interactive dashboards to monitor critical inventory metrics, providing real-time visibility and empowering cross-departmental strategic planning and operational adjustments.

Collaborated effectively with cross-functional teams, including procurement and finance, to deliver accurate data insights, successfully supporting internal audits and streamlining reporting initiatives.

Leveraged Python and SQL for advanced data manipulation and analysis, extracting key trends and patterns to predict future inventory needs and mitigate supply chain risks.

Education

Makerere University

Kampala, Central Region, Uganda
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BSc Quantitative Economics

Courses

Econometrics

Statistical Modeling

Mathematics

Business Intelligence

Languages

English

Skills

Programming Languages

Python, R, SQL.

Data Analysis & ML Libraries

Pandas, NumPy, Scikit-learn, Tidyverse, ggplot2, Prophet, K-Means Clustering.

Tools & Platforms

Excel, Git, Streamlit, ERP Systems, Dashboarding Tools.

Statistical & Analytical Methods

Statistics, Econometrics, Statistical Modeling, Forecasting, Data Collection, Data Analysis, Business Intelligence, Customer Segmentation.

Soft Skills

Team Collaboration, Stakeholder Communication, Data Storytelling, Problem-Solving, Strategic Planning.

Projects

Customer Segmentation

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Summary

Applied unsupervised machine learning techniques (K-Means Clustering) to segment mall customers based on demographic and behavioral data, providing actionable insights for targeted marketing strategies.

Demand Forecasting

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Summary

Developed a demand forecasting solution using Python and Prophet, analyzing historical retail sales data to build product-level models and present insights via an interactive Streamlit dashboard.