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AI Engineer // UCL 25' MSc Machine Learning
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Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
LLMs-from-scratch
October 29, 2025 – Present
My code as I work through the "Build a Large Language Model (from scratch)" by Sebastian Raschka
View Projectlanguage-of-the-markets
June 2, 2025 – November 20, 2025
Deep Reinforcement Learning trading agent (U-Net + Transformer) that fuses financial news sentiment with technical indicators. UCL MSc Dissertation (Distinction).
View Projectleveraged-treasury-strategies
May 3, 2025 – May 3, 2025
leveraged-treasury-strategies — GitHub repository
View ProjectAdvent-of-Code-2024
January 22, 2025 – January 26, 2025
I just found out about the Advent of Code, and this is my attempt at some of the problems. Obviously this is way after the fact, but I'm just attempting these for fun!
View ProjectFinetuned-RoBERTa-Emotion-Classifier
April 10, 2024 – April 10, 2024
Emotion Classifier with 94% accuracy on Twitter messages with six fundamental emotions: anger, fear, joy, love, sadness, and surprise.
View ProjectML-Notes
February 23, 2024 – February 26, 2024
Notes for various courses, books and videos on Machine Learning I am learning from in my journey to level up in ML
View ProjectNeural-Net-From-Scratch-with-Numpy-Fashion-MNIST-dataset
December 4, 2023 – December 4, 2023
Neural Net From Scratch with Numpy and Math (No PyTorch, TensorFlow etc...) on the Fashion MNIST dataset
View ProjectEEG-classification-using-CNN-on-Images
October 27, 2023 – October 27, 2023
Using CNN to classify EEG data that have been transformed into images. It classifies whether or not a participant understood a video they watched.
View ProjectBERT_0.1
March 3, 2023 – April 12, 2023
Investigating the Impact of Pre-training on Child Language Data for BERT Models and its Performance on Downstream Grammatical Tasks
View ProjectCultural Fit Analysis
The candidate's projects are primarily personal and academic, focusing heavily on advanced machine learning and deep learning research. This indicates a strong drive for technical depth and continuous learning, which could be a good cultural fit for a research-oriented or innovative team. However, the lack of team-based or collaborative projects makes it difficult to assess collaboration skills. The projects align well with a Data Scientist role, particularly one focused on ML/DL research and implementation.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The candidate's project descriptions suggest a self-driven individual with a strong learning curve in advanced ML topics.