Building scalable AI and data-driven solutions — from RAG pipelines to intelligent systems.
I am a Data Scientist with a Master's degree from Uppsala University, specializing in large language model applications and retrieval-augmented generation (RAG). This expertise was the focus of my master's thesis and was applied professionally in my role at Hypertype. My background includes developing predictive analytics at Ericsson, automating financial pipelines at EPIC InnoLabs, and building scalable systems with .NET, Angular, and Docker. Passionate about bridging research and application, I thrive at the intersection of machine learning, software engineering, and innovative AI solutions.
Focus: Machine Learning, Statistics, Image Analysis, Data Engineering
Thesis: Evaluation of RAG Pipelines in Customer Support AI Agents (at Hypertype)
Second Prize at TDK Scientific Students' Association Conference
Project: YOLO-based object detection system for pharmaceutical production
Contributed to the design and implementation of a new AI-driven customer support platform at Hypertype.
Created a system to benchmark and improve chatbot pipelines.
Developed an LLM-powered assistant to generate personalized educational content.
Built predictive models for telecom reliability.
Automated financial forecasting workflows.
Built a detection system for pharmaceutical quality assurance.
TDK Conference for Scientific Students' Associations (BME)