Luca Bella
Data & Software Engineer @Lakestar
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WORK HISTORY
Data & Software Engineer @Lakestar
Berlin, DE
Designed and developed internal investment intelligence platforms integrating Python-based ETL pipelines, LLM agents, and machine learning models.– Automated startup evaluation workflows, improving analysis speed and consistency.– Deployed scalable backend systems using FastAPI, Flask, MongoDB, MySQL, and Docker.– Built machine learning models for dealflow scoring and investment prioritization.– Implemented Retrieval-Augmented Generation (RAG), fine-tuned LLMs and set up MCP servers to enhance insights, automate due diligence, and manage dealflow.– Developed frontend applications within the internal platform using React, enabling seamless user interaction and visualization.
EDUCATION
Camplus College
Member of the University College of Merit "Camplus Lingotto"
TUM
Master of Science - MS
Universitat Internacional de Catalunya
Bachelor en Tecnología y Producción Industrial
liceo scientifico Galileo Galilei Catania
Liceo Scientifico
Politecnico di Torino
Bachelor's degree
ABOUT LUCA BELLA
I’m a Software and Data Engineer passionate about building intelligent systems that leverage machine learning, AI, and data engineering to transform how organizations make decisions. At Lakestar Venture Capital, I’ve been developing a comprehensive internal investment intelligence platform—end to end. From frontend interfaces to backend systems, I’ve designed, built, and deployed scalable applications that integrate data pipelines, machine learning models, and large language models (LLMs) to automate research, deal sourcing, and decision-making processes. My work sits at the intersection of software engineering, AI research, and data architecture, bridging technical complexity with strategic investment impact. I love turning messy, unstructured data into actionable insights and intuitive products that enhance human decision-making. Technically, I’m fluent in Python, SQL, and APIs, and experienced with FastAPI, React, Docker, and cloud infrastructure (AWS / GCP). I also work with MLOps frameworks, LLM fine-tuning, and end-to-end ML product deployment. I’m excited by roles that connect AI, software, and data systems—where I can help shape intelligent products from both the backend logic and the user-facing experience. Let’s connect if you’re building the next generation of AI-driven applications or looking for full-stack data engineers with strong AI/ML foundations.
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