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Schedule Interview NowMy name is Caina Max C. and I have over 10 years of experience in the tech industry. I specialize in the following technologies: Python, SQL, Linux, Data Science, Data Analytics, etc.. I hold a degree in Master of Business Administration (MBA), Doctor of Philosophy (PhD). Some of the notable projects I’ve worked on include: SQLDeps: LLM-powered SQL Dependency Extractor, AI-powered Cattle Mapping from High-Resolution Satellite Imagery, Mitigating Nonproductive Time: Asset Fault Detection, Machine Learning for Data Integrity at Scale, ProjectLens: An open-source Python library for project snapshots. I am based in Guarulhos, Brazil. I've successfully completed 5 projects while developing at Softaims.
I employ a methodical and structured approach to solution development, prioritizing deep domain understanding before execution. I excel at systems analysis, creating precise technical specifications, and ensuring that the final solution perfectly maps to the complex business logic it is meant to serve.
My tenure at Softaims has reinforced the importance of careful planning and risk mitigation. I am skilled at breaking down massive, ambiguous problems into manageable, iterative development tasks, ensuring consistent progress and predictable delivery schedules.
I strive for clarity and simplicity in both my technical outputs and my communication. I believe that the most powerful solutions are often the simplest ones, and I am committed to finding those elegant answers for our clients.
Main technologies
10 years
7 Years
7 Years
3 Years
Potentially possible
Google Brasil
I developed SQLDeps: An open-source Python package to map and visualize SQL dependencies with LLM-powered analysis. It accelerates analysis >150X while being over 400X more cost-effective! Try out the sqldeps-simulator to simulate the savings for your scenario.
AI-powered cattle mapping to combat Amazon deforestation. Deliverables: • Led a team of data science undergrad students • Downloaded and annotated >10k images and >100k cattle • Trained and optimized deep learning models to estimate cattle counts • Built a scalable system that can be applied to target regions like protected and embargoed areas These results empowered Brazilian companies and authorities to take legal action against illegal deforestation.
Industry: Oil and gas Goal: Predict asset failures before they happen and optimize maintenance. Solution: Data-driven framework using statistical models to detect failure intensity and location with over 98% accuracy. Outcome: - Model in production, saving hundreds of thousands of dollars annually. - Scientific publication at OnePetro
Machine Learning for Data Integrity: Validating Rural Property Identities in the Brazilian Amazon Business requirement: Provide an automatic and scalable way to validate the integrity of farm property groups generated by another process, as these groups are used in applied research on Amazon deforestation. End solution: I trained a binary classifier to flag ill-formed groups at scale, providing data insights and delivering an interpretable model with a high recall rate.
I developed ProjectLens: an open-source Python package that creates project codebase snapshots optimized for LLMs interaction. ProjectLens is a specialized tool for developers and teams who want to leverage AI assistants like ChatGPT, ClaudeAI, and DeepSeek for code analysis, documentation generation, and codebase understanding.
Master of Business Administration (MBA) in Data Science & Analitycs
2021-01-01-2023-01-01
Doctor of Philosophy (PhD) in Genetics and Evolutionary Biology
2016-01-01-2021-01-01