Position: Data Analyst
Category: Data Analyst
English level: upper
Years of experience: 2


Projects
Occurrence, risk assessment and elimination of chemicals of emerging concerns in wastewater treatment plants in Western Kenya.

In this analysis, I utilized R Studio to compute the removal efficiency of each water waste treatment plant using the dplyr and magrittr libraries. Firstly, I identified the chemical compounds with an influent value above 200 and conducted a descriptive analysis of the mean and standard deviation of each chemical compound in every water waste treatment plant.

Next, I computed the removal efficiency for each chemical compound and compound class in every water treatment plant and performed a comparative analysis to identify the most efficient plant for each chemical and compound class. To visualize the results, I used the ggplot2 package to create visually appealing charts depicting the removal efficiency for each wate

DATA SCIENCE JOB MARKET EDA – Personal Project	January 2023
Utilized Python to analyze 7000 data science job listings and gain insights on what it takes to land a job in analytics
Implemented Regex techniques to comb through the job descriptions and identified the key requirements 
Aggregated and visualized the data by using pandas, matplotlib and word cloud to compile a professional report
BENEFIT PACKAGE BENCHMARKING DASHBOARD – Virtual Client’s Project	February 2022
Created a dashboard with Power Bi to help clients compare different employee benefit packages
Transformed and processed client data by using DAX and Excel to ensure data completeness and validity
Provided technical insights on how the client can fully utilize their data by introducing different technologies 
Consulted with the client to determine the best metrics to be displayed on the final product
SENTIMENT ANALYSIS ON TWEETS – Personal Project	December 2021
Utilized R Studio to perform sentiment analysis on 14,000 tweeter reviews of six major airlines
Performed data cleaning and text analysis to successfully identified the major complaints for each airline
Applied regression and machine learning to produce a final model with an accuracy of 88% and lift of 34%
CUSTOMER SALES ANALYSIS – Personal Project	November 2021
Utilized SQL to extract data from 8 different related tables from customer sales databases using JOIN and VIEW
Transformed and filtered data by using aggregating and filtering functions to improve the reporting process
Loaded and visualized data with Python to identify key business intelligence that can improve sales performance