Hello, I'm

Moses Kamau Chege

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Transforming raw data into actionable insights

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About Me

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Statistician & Data Analyst

Driven by an insatiable curiosity and a relentless commitment to solving complex technical and business challenges, I bridge the gap between mathematical concepts, analytics, and data-driven insights. My journey is fueled by transforming raw datasets into intuitive visual platforms that optimize operational performance and strategic decision-making.

With expertise spanning interactive dashboard development, market intelligence, and predictive modeling, I specialize in end-to-end data workflows. From data pipeline architecture to crafting web applications, I have experience working with Python, R, SQL, Streamlit, Plotly, and Data Collection to deliver clear, actionable solutions for businesses.

Education & Certifications

Bachelor's Degree in Statistics

Laikipia University | Nyahururu, Kenya (2015 – 2019)

Top 5 in class (GPA: 67/100). Specialized in quantitative coursework, probability, databases, and statistical computing.

IBM Data Science Certificate

Coursera (Oct 2022 – Nov 2022)

Completed 400+ hours of rigorous coursework covering machine learning, data visualization, and applied data science capstones.

Google Data Analytics Certificate

Coursera (Mar 2021 – Jul 2021)

Completed 300+ hours of training focused on exploratory data analysis, data cleaning, and decision-making frameworks.

Featured Projects

KPC IPO Investor Insights

An interactive dashboard analyzing investor participation and insights from Kenya Pipeline Company IPO data.

Tenakata Loan Portfolio Analysis

An interactive analysis of loan portfolio distribution, risk, profitability and predictive insights.

Sendy Logistics Analysis

Data analysis project focused on understanding logistics operations and identifying insights from delivery data.

University Ranking Dashboard

Interactive R Shiny dashboard for exploring university ranking data and performance indicators.

Insurance Pricing Tool

Interactive R Shiny dashboard for simulating pricing strategies and visualizing customer segmentation insights.

Customer Churn Analysis

Analysis of customer churn patterns using a telecom dataset through visualizations and descriptive statistics.

Technical Skills

Python 80%
SQL (PostgreSQL) 80%
R 85%
SPSS & STATA 75%
Power BI & Tableau 80%
Streamlit & Plotly 75%
Data Analysis 95%
Machine Learning 85%
Statistical Modeling 85%
Data Collection 90%

Tools & Technologies

Python
R & R STUDIO
PostgreSQL
SPSS SPSS
STATA STATA
PBI Power BI
Jupyter
SPYDER Spyder
HTML5
CSS3
JavaScript
SQL SQL
VS Code
Git
GitHub

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