Senior Data Analyst
Barcelona-based, with 7+ years driving business value via data. Expert in the full data science workflow (SQL, R, Python, PowerBI, Looker), with a proven track record at HP. Passionate about solving complex problems with data and pioneering AI applications.
HP | 2023 - 2024 (1 year and 1 month)
HP | 2022 - 2023 (1 year and 2 months)
Visiolink | 2020 - 2022 (2 years and 3 months)
Visiolink | 2018 - 2020 (1 year and 8 months)
BSS International + Aarhus University | 2016 - 2019
Smart home automating 130+ devices (Home Assistant, Raspberry Pi) with local LLM (Ollama) for voice control.
Led design of Redshift data models at HP using SQL & LookML for global scan user behavior analysis.
Developed a multi-screen dashboard at Visiolink (Raspberry Pis, HTML/CSS/JS) for real-time KPI display.
Self-built 2D game (Phaser, Vite) for learning game dev & testing LLM-driven creative asset generation.
Aarhus University | 2017 - 2019
Key Coursework:
Nanyang Technological University, Singapore | 2016
Focus Areas:
Aarhus University | 2014 - 2017
Thesis: 'Analysis of consumer behavior in relation to autonomous vehicles' (Grade: A). Applied data analysis skills to a practical problem merging interests in new technology and consumer behavior.
Love exploring Montserrat and other mountains on my motorcycle.
Regularly play badminton and padel tennis to stay active.
I love IT, AI trends, new technologies, and home automation.
Always up for a challenge: Let's talk over a VR table tennis match!
Drag the icons from the bank below into the correct stage of a typical data analysis pipeline. Correctly connecting stages reveals the data flow!
I'm always open to discussing new projects, creative ideas, or opportunities to be part of something impactful. Feel free to reach out!
+45 27822422 / +34 653330518
linkedin.com/in/kasperheyst www.heyst.infoBarcelona, Spain
This ongoing personal project is a deep dive into the world of home automation and applied AI. Starting with a Raspberry Pi and Home Assistant, I've built a system that now controls and automates over 130+ devices throughout my home.
The current focus is on enhancing user interaction through natural language. I am integrating and optimizing a locally hosted Large Language Model (LLM) using Ollama with Home Assistant's "Assist" voice control pipeline. This allows for more intuitive and conversational control of smart devices.
Key Features & Technologies:This project not only satisfies my passion for technology but also serves as a practical testbed for exploring AI applications in a real-world setting.
As a Scan Program Analyst at HP, a key responsibility was to architect and implement comprehensive data models to analyze global scan data. This involved working with massive datasets related to how users interact with HP's scanning functionalities on both mobile and desktop platforms.
Objectives & Achievements:This project significantly enhanced HP's understanding of its scan ecosystem and directly contributed to efforts to improve user experience and product offerings.
During my time as an Analytics Consultant at Visiolink, I identified a need for better internal visibility of key performance and company information. I took the initiative to design, program, and install a multi-screen dashboard wall system.
The system utilized multiple Raspberry Pi units, each programmed to drive a specific display. I programmed them to ensure consistent content across screens. The dashboards themselves were web-based, built using SSH, HTML, CSS, JavaScript and some small APIs, allowing for easy updates and dynamic content integration.
Key Features & Technologies:This project successfully provided a centralized, dynamic visual hub for the Visiolink office, improving awareness of company performance and fostering a more informed environment.
This self-built 2D game was developed using JavaScript, Phaser, and Vite.
The core objectives were to learn game development principles and to explore the practical application of Large Language Models (LLMs) for generating game assets such as images, music, and video (using tools like ChatGPT, Suno, Gemini), complemented by custom sprite work in Photoshop. The project is self-hosted and managed via Filezilla.
Key Technical Learnings:This project significantly enhanced full-cycle web game development skills, particularly in JavaScript, Phaser, Vite, and the practical application of emerging AI tools.