Luca Fiume

• Architected and delivered an insights layer within the Databricks lakehouse, enabling multi-agent AI systems to autonomously generate business reports, forecasts, and strategic analyses for global Sport and Country Commercial Directors. • Engineered 10+ production-grade data models utilizing robust orchestration and automated testing frameworks, ensuring high data quality and low-latency retrieval for downstream agentic AI applications. • Spearheaded the migration and decoupling of a Modern Data Stack (dbt, Airflow, Databricks), successfully isolating infrastructure budgets between two major teams and driving a 20% reduction in operational costs.

- Diversified Machine Learning datasets by programming three python web scrapers obtaining 15 000 job postings - Performed Exploratory Data Analysis (EDA) and integrated 2,869 CoVID-19 affected job seekers data points into a Natural Language Processing (NLP) algorithm aiming at matching candidates with STEM career roles in London - Collaborated on two GitHub repositories making weekly Pull Requests to merge python code shared with a Senior data scientist and two backend developers working in an Agile Scrum environment and shipping code biweekly

During my Industrial placement year, I was selected to join the recently expanding Digital team in General Electric Oil & Gas. I was able to contribute in the following two capstone projects: - Brainstormed a manufacturing plant visitor induction solution‭ to cut business costs. Oversaw and developed in an Agile team the MySql Database‬ linking 32 venues and 1,200 daily visitors throughout the UK‬‬ - Updated stakeholders weekly, maintained contractor relations and main onsite point of contact for a network & hardware site migration project. Successfully relocating 500 manufacturing plant workers and the Aberdeen Stoneywood Subsea Systems HQ office including 450 workstations during a period of 10 months‬‬‬‬‬.