SERGIO SÁNCHEZ

Instructed students on the comprehensive data science pipeline, encompassing data acquisition, wrangling, exploratory data analysis, visualization, modeling, and optimization techniques.

Developed and delivered hands-on coursework in Python (pandas, scikit-learn, Spark) and R, emphasizing reproducibility, ethical considerations, and effective communication of data science findings.

Mentored and supervised student projects, guiding the application of advanced statistical and machine learning methods to solve complex real-world datasets and challenges.

Architected and deployed a multi-agent AI assistant, leveraging Vercel AI SDK, Next.js, Supabase, and Coolify, to provide comprehensive analysis of parliamentary activity and public discourse.

Developed an AI-powered answer engine utilizing LangGraph, LangChain, LlamaIndex, Chainlit, and GCP to perform deep research, cross-source synthesis, and accurate citation tracking.

Engineered automated data pipelines using Prefect to extract and scrape interventions from all members of the Spanish Congress, exposing data via a multi-platform application supporting keyword and semantic querying.

Fine-tuned a Spanish BERT model from HuggingFace's Transformers to accurately classify political bias in tweets, facilitating granular geographic analysis of voting intentions.

Designed and implemented robust automated data pipelines using Airbyte, dbt, and Airflow to efficiently ingest diverse data from multiple social platforms into a centralized AWS data warehouse.

Led product strategy and architectural design for the Ultralytics HUB mobile app, enhancing user experience for data browsing, label/statistic inspection, and YOLO model management.

Enabled on-device, real-time inference capabilities within the Ultralytics HUB mobile app, allowing users to download and execute trained YOLO models directly.

Engineered native Android/iOS SDKs (Java/C++/Swift) to integrate real-time YOLO model inference for classification, detection, and pose estimation.

Developed an open-source Flutter plugin, extending real-time YOLO model inference capabilities to cross-platform applications, significantly broadening accessibility.

Architected and led the full development lifecycle of a secure mobile banking application, collaborating with stakeholders to define requirements, align UX, and ensure scalable delivery.

Directed end-to-end development of a social network application for a non-profit, implementing dynamic post feeds, event organization, job boards, and chat functionality within a modular, maintainable architecture.

Spearheaded the end-to-end development and successful release of a sports social network application, managing the entire lifecycle from design to deployment.

Architected and implemented a highly scalable Firebase backend infrastructure, effectively supporting diverse social features and user growth.

Developed and implemented comprehensive inventory and expense-tracking applications, overseeing end-to-end design and feature implementation.

Architected a scalable Firebase backend and crafted intuitive UI/UX interfaces, ensuring alignment with product specifications and user experience requirements.

Engineered the Android frontend for a sports social network application, utilizing Java/Kotlin to deliver a seamless user experience.

Supported backend maintenance operations and contributed to the design of user-centric UI/UX interfaces, enhancing application functionality and user engagement.