Hello, I'm Dave Karanja

QA & QE Trainee

I’m currently growing my skills as a QA & QE trainee, with a focus on creating software that’s both dependable and user-friendly. This portfolio is a glimpse into my learning journey, the projects I’ve contributed to, and the areas I’m working to improve. I look forward to connecting and sharing ideas with others who value quality in technology

About Me

I’m an actuarial science student at DeKUT with a growing interest in technology, particularly data science and analytics. I’m currently training as a QA and QE analyst, learning how to improve the reliability and performance of software. Outside my studies, I enjoy exploring cars, watching movies, swimming, cycling long distances, and playing games like pool and poker. Recently, I’ve also started learning chess, which has been a fun new challenge.

What I Do

Software Development

So far, I’ve built websites using HTML, CSS, and JavaScript. I’m still in the learning curve of this path, exploring new ways to improve my skills and create better projects as I grow.

QA Testing

Quality assurance is the focus of my current training. While I’m not practicing it yet, by the end of this three-month program I’ll have the skills to test, review, and improve software as part of my work

Model Building

I’ve worked on several projects that involve building models. This includes sourcing and cleaning data, exploring it to understand its structure, and checking if it fits the model requirements. From there, I build a baseline model, evaluate and validate its performance, and, in some cases, deploy it as a wrapped function.

Education

Bachelor of Science in Actuarial Science

Dedan Kimathi University of Technology, Sep 2022 – Dec 2025
Completed the coursework and now awaiting graduation. Some of my notable skills include working with R and LaTeX, financial analysis, statistical modeling, Bayesian statistics, and survival analysis.

High School

St Joseph's High School Githunguri,
Jan 2018 – April 2022
This is where my passion for working with numbers and computers began, shaping the path I’ve continued to follow

Certifications

This section will showcase the certifications I’ve earned. It’s still a work in progress as I prepare to add the relevant details and links.

Experience

QA & QE Trainee

Sep 2025 - Dec 2025 | Nyeri, Kenya

Currently undertaking foundational training in web development, covering both front-end and back-end technologies.
Learning the fundamentals of HTML, CSS, and JavaScript to build responsive user interfaces.
Preparing for software testing by starting with manual methods and progressing into automation tools
Building teamwork and problem-solving skills through collaborative projects and practical exercises.

Investment Attache

Sep 2024 - Dec 2024 | Nairobi, Kenya

Strengthened communication skills through regular client interactions and professional correspondence.
Enhanced technical proficiency by improving Excel expertise, learning SAP software, and preparing financial reports and summaries.
Gained practical exposure in investment and finance concepts while also drafting legal documents to support organizational operations.

Applied Data Science

Jan 2025 - Jun 2025 | Remote

Completed the Applied Data Science course, working on 8 projects that addressed real world problems in housing, environment, finance, and risk analysis.
Applied techniques such as data cleaning, visualization, regression, clustering, time-series forecasting, and statistical testing using Python, SQL, and MongoDB.
Built models to analyze, predict, and interpret outcomes, and deployed solutions including a web API for volatility forecasting.

Projects

Forecasting Stock Market Risk Using MRS-GARCH Model

GitHub Live

This project analyzed six NSE stocks (CTUM, EABL, EQTY, KCB, SAFARICOM, and KPLC) from January 2019 to June 2025. After sourcing the data, I explored price trends, computed log returns, and fitted ARMA models to establish the mean equations for GARCH. Using AIC and BIC, the GED distribution proved most suitable across all stocks. I then compared GARCH extensions (EGARCH, GJR-GARCH, FIGARCH) under GED and incorporated the best fits into an MRS-GARCH framework to capture regime shifts in volatility. Backtesting for Value at Risk (VaR) and Expected Shortfall (ES) showed that MRS-GARCH provided the most reliable forecasts, outperforming the standard and extended GARCH models.

R
Latex

Skills

React JS

HTML

CSS

Python

Git

Get in Touch

Fill out the form and let's see where collaboration takes us. You can also call me or reach out via email.

+254 111 924 972

Nairobi, Kenya

davekaranja6@gmail.com