Anas HAMOUTNI
Statistical Engineer | Applied Mathematician
Casablanca, Morocco
Statistical Engineer | Applied Mathematician
Casablanca, Morocco
I am a statistical engineer with 5 years of experience applying statistical modeling and machine learning to solve real-world problems across multiple industries. I hold an engineering degree in Actuarial Science & Quantitative Finance from INSEA (Rabat), where I built a strong foundation in probability theory, stochastic processes, and mathematical optimization.
My day-to-day work focuses on building predictive models, conducting statistical analysis, and developing data-driven solutions for complex business challenges. I am an Associate Member of the Moroccan Association of Actuaries (AMA).
GLMs, regression analysis, hypothesis testing, Bayesian inference
Supervised/unsupervised learning, deep learning, NLP, computer vision
Linear algebra, calculus, optimization, probability theory
Python, R, SQL, TensorFlow, scikit-learn, pandas
I have worked in actuarial consulting with leading insurance companies across Africa and the MENA region, including clients such as Allianz, AXA, and Sanlam. My expertise covers P&C pricing with GLM models, reserve estimation (IFRS 17, Solvency II), and enterprise risk analysis. This experience has strengthened my ability to apply rigorous statistical methods to complex, high-stakes business problems where accuracy and reproducibility are essential.
I started Kudos AI as a way to document what I learn and share it in a format that I wish existed when I was starting out: tutorials that combine the math, the intuition, and the code in a single place. Every article on this site is written from my own study notes and consulting experience.
The blog covers topics I work with professionally and study in my own time, including natural language processing, computer vision, time-series forecasting, and the latest developments in large language models. Each tutorial is paired with a Jupyter notebook on GitHub that you can run on Google Colab with one click.
Beyond written tutorials, I have built a collection of interactive browser games that teach AI concepts through hands-on play, from guessing ML vocabulary (Neurdle) to visualizing gradient descent (Gradient Golf). The goal is to make machine learning accessible to anyone willing to invest the time, regardless of their starting point. Whether you prefer reading a detailed breakdown or learning by playing, I believe the best way to understand a concept is to engage with it actively rather than passively.