About Me
I’m an aspiring Data Scientist.
Who am I?
Hey there — I’m Natnael Getahun, a fourth-year Statistics student at Addis Ababa University who’s obsessed with numbers, data, and all the stories they can tell.
I started as a young boy who obsessed over math problems he couldn’t solve. I continued to Statistics in the hopes of finding real world application of mathematics. Along the way, I discovered two worlds that completely changed the game for me: artificial intelligence and finance. Now, I spend a good chunk of my time exploring how data can be used to make smart predictions — stock prices, market trends, economic shifts, you name it. There’s something deeply satisfying (and yeah, a little bit like having a superpower) about using raw numbers to anticipate what’s coming.
I’ve been deep in the weeds with personal and academic projects that bring math, code, and markets together. From building financial forecasting models to experimenting with machine learning, I treat every project as a chance to learn something new — and hopefully build something useful.
It is clear to me that we need to develop a safe and controllable AGI. I have my doubts about the power of regulations to control AI in a world whare many countries have their own different agendas. I believe the answer to controlling AI lies in mathematics and statistics, its foundations. I plan to contribute to the development of safe AGI in any possible way I can.
This site is where I share what I’ve been working on, thinking about, or sometimes just what’s been keeping me up at night. I’m especially interested in short-term trend prediction, making data-driven investing more accessible, and using AI in ways that go beyond buzzwords.
If you’re working on something cool in data science, finance, or AI, let’s talk.
Thanks for stopping by!
My Blog
Coming Soon!
Coming Soon.
Read moreMy Project Portfolio
Factors Affecting the Current Capital of MSEs: A Multiple Linear Regression Approach
In this project, I investigate the determinants of success for Micro and Small Enterprises (MSEs) in Ethiopia. I walk through a rigorous econometric process, addressing heteroscedasticity through log transformations and Weighted Least Squares (WLS), finally achieving a model that explains 81.6% of capital variability.
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