Data Analyst & Scientist

Clinton Munene

Turning Raw Data Into Strategic Decisions

Experienced data professional with expertise in analytics, pipeline engineering, and business intelligence. I help organisations unlock insights from complex datasets to drive measurable outcomes.

3+
Years Experience
20+
Projects Delivered
5+
Tools Mastered
CM

Data-driven professional with a passion for insight

I am a Data Analyst and Scientist based in Nairobi, Kenya, with a strong background in transforming complex datasets into actionable business intelligence. My work spans data pipeline development, machine learning, predictive analysis, dashboard creation, and statistical analysis.

I thrive at the intersection of engineering, visualization and analytics — building robust data infrastructure while keeping the business question front and centre.

Data Analytics
KPI dashboards, trend analysis, reporting
Data Engineering
ETL pipelines, SQL databases
Business Intelligence
Power BI, Tableau, executive reporting
Programming
Python, SQL, R, pandas

Tools and Technologies

Analytics & BI

Power BI90%
SQL88%
Excel / Google Sheets92%
Tableau75%

Engineering & Programming

Python (pandas, numpy)85%
Data Pipelines / ETL80%
Streamlit82%
Git / Version Control78%
R-Programming78%

Also familiar with

Artificial Intelligence Data Cleaning Plotly Seaborn Scikit-learn Front End Development Machine Learning

Featured Projects

A selection of data projects spanning analytics, Machine Learning, Artificial Intelligence and visualisation.

01
PythonStreamlitpandas

Construction Site Daily Progress Reporting

Real-time daily progress reporting system with Safety, and DPR modules. Tracks crew counts, incident trends, work completion_% and equipment hours with interactive visualisations.All are updated the moments it happens. This system ensures all incident never go unseen as the report is submitted daily

02
PythonPandas, seaborn, Scikit-learn, matplotlibETL

Ecommerce Growth Driver Analysis-Linear Regression

This project turns a common business dilemma — mobile app vs. website investment — into a data-driven answer. Using linear regression on real customer behaviour, I identified that the mobile app generates 37x more revenue impact per minute than the website, and that long-term membership retention is the single biggest growth lever the company had.

03
PythonpandasPlotly

Housing Price Prediction Model

Machine learning pipeline to predict housing prices using historical data. Includes feature engineering, model evaluation, and an interactive results dashboard. The model is fast and less expensive as ccompared to human appraisers or agents who typically sets the prices.The solution this project proposes is to train a machine learning model on historical house sales so that, given a new house's attributes, the system can predict a fair market price automatically, consistently, and at scale — removing guesswork from one of the biggest financial decisions people ever make.

04
Pythonpandas, matplotlib, streamlitPlotly

Labour Productivity and cost-efficiency Analyzer

Analyzes construction labour productivity and cost-efficiency patterns, with interactive dashboards highlighting cost drivers and performance metrics.

05
PythonpandasPlotly

Worker Productivity Dashboard

Interactive dashboard tracking individual and team worker productivity metrics, enabling managers to identify performance gaps and optimize workforce allocation.

06
PythonFastAPIpandas

Data Cleaning API

REST API for automated data cleaning operations including missing value handling, duplicate removal, and type standardisation — deployable for any data pipeline.

07
PythonNLPStreamlit

Sentiment Mode API

NLP-powered sentiment analysis API that classifies text as positive, negative, or neutral — useful for customer feedback, social media monitoring, and review analysis.

08
PythonNLPStreamlit

Sales Analytics Dashboard

A sales dashboard is only as good as the story it tells — and most tell the wrong one. This dashboard cuts through cluttered spreadsheets and disconnected reports to give sales teams and managers a single, real-time view of revenue performance, pipeline health, and target attainment. Built with Power BI, it tracks key metrics across products, regions, and time periods with interactive filters and live visualisations. From daily standups to quarterly reviews, it puts the right numbers in front of the right people at exactly the right time.

09
PythonStreamlit

Sales and Revenue Performance Analyzer

Most businesses know their revenue number — few understand what's actually driving it. This Sales & Revenue Performance Analyser transforms raw transactional data into clear, actionable intelligence across products, regions, sales reps, and time periods. Using Python, Pandas, and data visualisation, it surfaces the trends, gaps, and growth opportunities hidden inside your numbers. The result: faster decisions, smarter resource allocation, and a business that grows with evidence, not instinct.

Let's Work Together

Open to data analyst, data science, statistics, research analyst and BI developer roles. Let's connect.

Email
clintonmunene2000@gmail.com / clin37007@gmail.com
Location
Nairobi, Kenya
LinkedIn
linkedin.com/in/clinton-munene
GitHub
github.com/Clinton-Analyst
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