Giulia Gallo

GIULIA GALLO, PH.D --LinkedIn.com/giuliagallo DATA & AI EXPERT EDUCATION PROFILE PH.D, COMPUTER SCIENCE University of Genoa 2010 — 2013 Data & AI expert with a Ph.D. and 10+ years delivering scalable analytics solutions, leading strategic cloud initiatives, and driving innovation across data science and engineering. MASTER’S DEGREE, BIOENGINEERING University of Genoa 2007 — 2009 BACHELOR'S DEGREE, BIOMEDICAL ENGINEERING University of Genoa 2004 — 2007 SKILLS Technical Azure Cloud (Azure ML, Databricks, Synapse, Purview) Microsoft Fabric Python (Pyomo, PySpark, Pandas, scikitlearn) Machine Learning (Classification, Regression, Forecasting, NLP, Optimization) Generative AI and Retrieval-Augmented Generation (RAG) Big Data Technologies (Apache Spark, Hadoop) Data Engineering (ETL/ELT, Azure Data Factory, SQL) Docker and Kubernetes Power BI and Power Apps Git and Azure DevOps Solution Accelerators & Technical Documentation MLOps Professional Skills Project & Program Management Strategic Planning & Advisory Customer Engagement & Presales Technical Writing & Communication Cross-Functional Leadership Rapid Upskilling & Adaptability Innovation & Problem-Solving WORK EXPERIENCE DATA & AI SENIOR TECHNICAL SPECIALIST Microsoft | 2024 — 2025 Strategic AI & ML Solutions: Led multiple strategic customer engagements, showcasing Azure AI capabilities through tailored demos and proof-of-concepts (PoCs). Successfully conducted Azure AutoML demonstrations to effectively highlight Azure’s competitive advantages, driving deeper customer adoption. Generative AI & Azure OpenAI Leadership: Initiated and spearheaded innovative customer engagements leveraging Azure OpenAI, notably orchestrating the first Azure OpenAI Prompt-A-Thon for a major education support technology company, successfully identifying multiple AI-driven use-cases. Managed subsequent architecture development and PoC/MVP implementations, positioning Azure as a central AI partner for educational and business applications. AI Product Development & Deployment: Actively engaged in developing and demonstrating minimum viable products (MVPs) for chatbots and document-review applications using Azure AI technologies, significantly enhancing customer understanding and adoption of Microsoft AI capabilities. Cross-functional Collaboration & Customer Engagement: Expanded internal and external networks by participating extensively in strategic meetings with specialists, account executives, and customer teams, significantly strengthening collaboration and aligning Azure solutions with customer business objectives. DATA & AI SENIOR CLOUD SOLUTION ARCHITECT Microsoft | 2021 — 2024 End-to-End Data Science Solutions: Led proof-of-concept developments and deployments for major enterprise customers, significantly increasing their Azure Consumption Revenue (ACR). One project notably grew from $200/month to $4,190/month within a single fiscal year through strategic implementation of AI solutions. Technical Leadership & Innovation: Authored influential Azure Architecture Center (AAC) articles focused on Customer Lifetime Value, Sports Analytics, and Inventory Optimization. These articles directly attracted new customers across diverse sectors (education, sports analytics, manufacturing), bolstered Azure’s market visibility, and served as foundational resources for broader adoption. Solution Accelerator Development: Directed a rapid and comprehensive overhaul of the Microsoft US (MSUS) Supply Chain Management Solution Accelerator. Built from scratch an advanced optimization model using Pyomo and Ray, and independently acquired new competencies (Power BI, Power Apps, Docker, Kubernetes) to swiftly complete UX/UI enhancements ahead of schedule. Strategic Project Management: Actively managed a team of senior Cloud Solution Architects (CSAs), organizing workflow, overcoming technical blockers, and successfully realigning and delivering stagnant high-priority initiatives. GIULIA GALLO, PH.D DATA & AI EXPERT WORK LANGUAGES English Italian EXPERIENCE CONTINUED Data Science & Engineering Integration: Facilitated seamless migration of complex customer data science workloads from legacy systems (e.g., R-based models) to Python-based solutions on Azure ML. Demonstrated Azure’s equivalency or improvement in predictive accuracy, significantly reducing customer deployment timelines. Cross-Team Collaboration & Enablement: Played a pivotal role in multi-team collaborations across Microsoft’s Intelligent Analytics Scenario, EDU, and Azure Purview engagements, notably contributing to high-profile proof-of-concepts that CERTIFICATIONS Azure AI Fundamentals (AI-900) Wharton Online - AI for Business Azure Fundamentals AZ-900 influenced strategic adoption decisions by major global companies. Thought Leadership & SME Contributions: Regularly provided expert guidance on optimization modeling and Responsible AI (RAI), contributing to internal Microsoft knowledge-sharing initiatives, reviewing research proposals, and advising teams on leveraging Azure ML for optimization problems. MLOps adoption: Collaborated with customer engineering teams to implement MLOps frameworks leveraging Azure ML pipelines, enhancing reproducibility and automated model deployment workflows. DATA SCIENTIST AWARDS 2014: NREL Director’s Postdoctoral Fellowship The NREL Director’s Fellowship attracts the next generation of exceptionally qualified scientists and engineers with outstanding talent and credentials in renewable energy research and related disciplines. Research grant: 600,000 USD (2 years) + 20,000 USD individual research allowance. Herbalife Nutrition | 2019 – 2021 End-to-End Data Science Solutions: Developed customer recommender systems using Apache Spark; improved churn prediction accuracy by 5% with Azure ML models. Led Capacity Engineering initiative using Azure AutoML, SQL, Python, and Splunk to forecast datacenter CPU usage. Established deployment best practices for production-level AI and Data Science solutions. Maintained and monitored production AI solutions, continuously optimizing model performance and operational efficiencies over a two-year deployment lifecycle. SENIOR SCIENTIFIC ENGINEERING ASSOCIATE Lawrence Berkeley National Laboratory | 2016 – 2019 Energy Systems and Market Analysis: Co-led DOE-funded research evaluating economic impacts of U.S. regional and inter-regional transmission planning. Led technical studies on renewable energy valuation in India and hydrogen energy system competitiveness in current energy markets. Directed analysis of wildfire economic impacts on power systems within the Western U.S. Co-led California Public Utilities Commission projects on technology pathways and market integration for demand-response and load-shifting. NREL DIRECTOR’S POSTDOCTORAL FELLOW National Renewable Energy Laboratory | 2014 – 2016 Advanced Energy Modeling & Research: Principal Investigator on integrated agent-based, machine learning-driven frameworks for renewable energy market behavior analysis. Led economic analyses of market dynamics, generator fleets, and ancillary reserves on revenue sufficiency.