Nicholus Muthomi

Nicholus Muthomi_

Data Scientist, Data analyst

PHONE:
+254 793 8434066
EMAIL:
muthominicholus22@gmail.com
ADDRESS:
107-10406 Timau, Kenya

Hi_

I am a Data Scientist & Analyst with 2+ years building machine learning models, automations and dashboards. I help businesses make sense of their data by building unique systems and tools around their specific issue, making decision making faster, clearer and more reliable. The final build is easy for everyone on your team to work with, not just the technical side.

If you are a business, let the work on this page speak for itself. If you are looking to hire, you are already in the right place.

DOWNLOAD CV

Services_

PREPROCESSING DATA

Cleaning and preparing raw data by handling missing values, outliers, encoding and normalisation to make sure analysis is built on solid ground.

VISUALISATION

Building dashboards and charts in Matplotlib, Seaborn, Plotly, Power BI and Excel that give decision-makers a clear picture of what the data is saying.

MODELLING

Building and training machine learning and deep learning models that solve specific business problems, from classification and regression to neural networks.

FEATURE ENGINEERING

Improving model performance by creating meaningful variables from existing data through transformations, aggregations and domain-specific calculations.

COMMUNICATION

Writing clear reports and presenting findings to both technical and non-technical audiences in plain language that leads to action.

24/7 SUPPORT

Available for urgent data needs, dashboard maintenance, model updates and new projects across time zones.

Resume_

05/2023 - 02/2024

Field Data Researcher

Mount Kenya Ewaso Water Partnership

Collected and analysed household data on farming practices and fuel usage. Led farmer training sessions contributing to a 40% reduction in firewood use and a 25% increase in farm productivity.

2023 - 2025

Certificate in Data Science

African Leadership Experience

Developed practical skills in statistical analysis, machine learning and data visualisation using Python, SQL, Excel and Power Bi that have enhanced my analytical and problem-solving abilities for practical projects.

Skills_

DATA ANALYSIS

Excel

95%

SQL

90%

PowerBI

85%

R

90%

DATA SCIENTIST

Python

90%

NLP

85%

Machine Learning

85%

Deep Learning

90%

Work_

Real-Estate Workforce HR Dashboard

Built an HR dashboard visualising headcount, gender mix and seniority. Revealed payroll and staffing trends, cutting project turnaround to 61 hours with a 97.45% task completion rate.

Demo

Market Volatility

Built a deep learning model for Google stock price prediction using 20 years of historical data, moving averages and volatility indicators. Deployed that model as a Streamlit dashboard for live forecasting.

View Project Demo

Spotify Analysis

Analysed 20K+ tracks to identify audio features driving popularity. Energy, danceability and loudness came out as the strongest predictors of viral success. Cross-referenced Spotify and YouTube data to inform release strategy.

View Project

Retail Store Analysis

Analysed 2,000+ US retail transactions to identify what drives revenue and margins. Electronics led on revenue, Beauty on margins. Seasonal peaks and high-value customer segments pointed to where campaigns should focus.

View Project

Brazil Olist

Analysed 100K+ Olist orders to find where sales and logistics could improve. Identified regional growth patterns, delivery delays and customer segments by behavior.

View Project

E-commerce Sales Analysis

Used K-means clustering to segment e-commerce customers by spending, returns and behavior. identified high-value segments and used that to improve targeting and retention.

View Project

Fifa Cup 22 Analysis

Processed data on 16K+ players to find performance patterns. Built player similarity algorithms using K-means and hierarchical clustering to support scouting and team selection decisions.

View Project

Transportation Logistics Dashboard

Built a dashboard tracking driver income, trips, expenses, cargo types and route performance. Monthly cost and performance data gave managers what they needed to make better scheduling and route decisions.

Demo

Customer Support & Banking Services Dashboard

Built a dashboard tracking service KPIs across banking products. Raised SLA compliance to 94% with a 92% overall resolution rate across six cities in UK.

Demo

Movie Recommendation System

Developed a filtering recommendation system that predicts user preferences by evaluating user ratings. Implemented as a customised recommendation web application with Streamlit.

View Project Demo

Hilton Hotel Sentiment

Analysed 5,000+ Hilton London reviews using NLP and machine learning, achieving 89% accuracy. 72% of reviews were positive. Staff service and room cleanliness came up most in the negative set.

View Project

Telco Customer Churns

Built an ML classification model predicting customer churn from usage and account data, achieving 79% accuracy in identifying customers likely to leave.

View Project

Flight Price Predictions

Built a model predicting Indian flight ticket prices from historical booking data. Deployed a Streamlit app where users can estimate costs for different travel scenarios.

View Project Demo

Saudi Service-Request & Payout Portal

Built a Power BI dashboard tracking 562K+ SAR in payouts across 560 service requests, broken down by service type, region and month. Riyadh accounted for 23% of requests with an average of 4.38 daily requests.

Demo

UK Online E-commerce

Conducted RFM and market basket analysis on 500K+ transactions to segment customers and identify cross-selling opportunities. The top segments accounted for 80% of revenue and product affinities that informed campaign decisions.

View Project

Project: Feild Data Researcher at MKEWP Company

Reliable, committted, thorough and easy to work with. Delivered clean work from the word go and never needed to be pushed. Would work with him again.

HR ~ Dennis Kimathi

Latest Posts_

Get in touch_

Phone:
+254 793 8434066
Email:
muthominicholus22@gmail.com
Book:
Schedule Meeting

Or just write me a letter here_

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