Resume

Professional summary, research profile, and selected experience.

Machine Learning Engineer and statistics researcher with experience in applied machine learning, evaluation methods, NLP, and data products.

Summary

  • Machine Learning Engineer working on end-to-end ML solutions, data workflows, and production-oriented analytics.
  • Researcher focused on clustering evaluation, item response theory, and probabilistic modeling.
  • Citation name: Ferreira-Junior.

Experience

Machine Learning Engineer, Kunumi

  • Worked on machine learning solutions for business problems with an emphasis on reliable delivery.
  • Built and improved ETL processes, explainable ML solutions, and cloud-oriented workflows.
  • Main tools included Azure Data Lake, Databricks, Spark, Pandas, and Python.

Jr. Data Scientist, Sem Processo

  • Developed regression, classification, and NLP models.
  • Worked on survival-analysis-based risk modeling, forecasting workflows, dashboards, and internal platform support.

Data Scientist Intern, Sem Processo

  • Supported predictive modeling and statistical analyses for applied business problems.

Research and publications

  • CLAIRE. Journal publication in Machine Learning (2025). DOI
  • Evaluating regression algorithms at the instance level using item response theory. Knowledge-Based Systems (2022). DOI
  • β⁴-IRT. arXiv preprint on enhanced discrimination estimation. arXiv
  • Iris-CV. BRACIS 2021 conference paper. Springer

Education and interests

  • B.Sc. in Statistics
  • Interests: machine learning, item response theory, clustering evaluation, trustworthy AI, and scientific software

Workshops and teaching material

  • Latent Ability. Browsable workshop site prepared for a University of Bristol session with Professor Ricardo Prudencio, including notes, activities, answers, and supporting navigation for latent-ability-aware evaluation in machine learning. Workshop site