Tech Lead | Software Engineering & AI Governance | Global Operations

I bridge the gap between complex business requirements and technical execution. With 15+ years of experience leading global operations, crisis response, and digital transformation in hyper-scale companies (Meta, GE, AB InBev), I am currently applying my executive background to Software Engineering, Data Science, and AI Risk Management.

My focus is on building responsible AI systems, optimizing data workflows, and leading agile engineering teams with a strong emphasis on governance and business impact.

• Academics: Incoming MSc Student in Computer Science at UFBA (Universidade Federal da Bahia), focusing on Applied Computing and Data Science. Recently concluded an MBA in Software Engineering at USP with a perfect score (10/10) on the final capstone research, earning an official nomination for the 'Best Thesis Award' among the cohort.
• Machine Learning & Data: Developing predictive models with Python, focusing on Explainable AI (XAI) and production risk assessments (Data Drift, Concept Drift).
• AI Governance & Security: Applying frameworks for responsible AI, compliance, and cybersecurity (certified by LSE, Duke, and Vanderbilt University).

• Languages: Python (Pandas, NumPy), SQL, HTML/CSS/JS (Basics).
• Data Science & ML: Scikit-Learn, Random Forest, Gradient Boosting, SHAP, LIME, Matplotlib, Seaborn.
• Architecture & Automation: APIs, n8n, Make, CRISP-DM framework.
• Security & Ops: Cloud Computing, Cisco CyberOps, MLOps concepts, Agile (Scrum/Kanban).

• Credit_Score_ML: An end-to-end predictive model for credit score classification built in Python. Incorporates Explainable AI (SHAP) for business transparency and outlines governance recommendations for MLOps deployment.

• LinkedIn: https://www.linkedin.com/in/fmaglopes/
• Languages: Portuguese (Native), English (Fluent), Spanish (Fluent), Italian (Fundamental), Mandarin (Beginner).