Nercino Neto is a Software Engineer at ALPB and a Data Scientist at LEMA, UFPB. With 3 years of experience, he specializes in technical architecture and developer marketing. Nercino is currently developing the ODS Racial project for Brazil's Ministry of Racial Equality and building the SIDTec-PB data intelligence platform. He also architects backend services and APIs for public transparency at ALPB. Nercino is seeking co-founders, founding engineers, and investors, and is open to speaking opportunities.

Product review, technical architecture, developer marketing, co-founders (technical), co-founders (business), founding engineers, investors, speaking opportunities, data intelligence platforms, ETL pipelines, backend services, public transparency solutions, AI-integration.

Currently developing the ODS Racial project for Brazil's Ministry of Racial Equality and building the SIDTec-PB data intelligence platform at LEMA/UFPB using Python and Apache Airflow for ETL. At ALPB, architecting backend services and APIs for public transparency using Java, Spring Boot, and PostgreSQL. Key technical activities include containerizing environments with Docker, designing database models, and implementing data pipelines and dashboards for mobile and web applications.

a Data Scientist Intern at Petlove, based in João Pessoa, Paraíba, Brazil. He is also pursuing a degree in Ciência de Dados para Negócios (Data Science for Business) at Universidade Federal da Paraíba. Gabriel has approximately two years of experience in data science, with a focus on technical architecture. His current projects include developing the ODS Racial platform for Brazil’s Ministry of Racial Equality, utilizing data warehousing and visualization techniques. At Petlove, his work involves data science tasks using Python and SQL, building ETL pipelines with PySpark, Spark, and Airflow, managing data with Hive and MongoDB, and deploying models via Docker. He has also worked on projects like EmpregAI and NAVI, which employ NLP, TensorFlow, and Big Data technologies for predictive modeling.

Technical architecture, data warehousing, ETL pipelines, machine learning, NLP, big data technologies, predictive modeling, data visualization, PySpark, Airflow, Docker, TensorFlow, cloud infrastructure.

Currently developing the ODS Racial platform at LEMA/UFPB for Brazil’s Ministry of Racial Equality, focusing on data warehousing and visualization. At Petlove, work involves data science tasks using Python and SQL. Key technical activities include building ETL pipelines with PySpark, Spark, and Airflow, managing data with Hive and MongoDB, and deploying models via Docker. Projects like EmpregAI and NAVI leverage NLP, TensorFlow, and Big Data technologies for predictive modeling.

Pedro Henrique Medeiros Vieira is a Data Scientist at DHARMA-AI, with 3 years of experience. He is currently working on building SSLMs and RAG agents, with key projects including Cirrosifier, ELT-SISU-DLDP, and Consumidor-Gov. His tactical tasks involve implementing ML models and data pipelines using Python, PySpark, TensorFlow, and LightGBM, as well as computer vision with OpenCV, YOLO, and SAM, and orchestration via n8n. Pedro is employed and open to work, seeking co-founders (technical), founding engineers, and speaking opportunities. He is open to introductions and prefers to be contacted via email.

SSLMs, RAG agents, Technical architecture, Machine learning, Data engineering, Computer vision, NLP, ETL pipelines, Product review, Partnerships, Founding engineers, Technical co-founders

At DHARMA-AI, current work involves building SSLMs and RAG agents. Key projects include Cirrosifier (medical ML classifiers with a Streamlit app), ELT-SISU-DLDP (Airflow and Docker-based ETL pipelines using MongoDB), and Consumidor-Gov (supervised learning with a Streamlit interface). Tactical tasks involve implementing ML models and data pipelines using Python, PySpark, TensorFlow, and LightGBM, alongside computer vision work with OpenCV, YOLO, and SAM, and orchestration via n8n.