Samuel Morais da Silva

About Samuel Morais da Silva

Currently, he is a data science expert consultant at MJV. He has been involved in data product solutions across various sectors, mostly in the financial, retail, energy, supply chain, legal, and healthcare markets. The projects he has worked on range from data architecture/engineering, investigative analyses to the development of complex machine learning models. He focuses on problem-solving using data products, such as real estate pricing, analysis of legal texts and official journals using statistical tools, machine learning, and deep learning.He is engaged in legal score modeling, employee performance, company activities, credit, assets, liabilities, and fraud classification (execution fraud, creditor fraud, and disregard of legal personality - DPJ). He is proficient in SQL, SQLite, MongoDB, Postgres, Redshift, Hadoop ecosystem, Hbase, and Hive databases. He also manages a data group, handling backlogs and activity prioritization with an agile methodology. Strong hands-on experience with Databricks, including Databricks SQL, notebooks, dashboards, and scalable data analytics solutions. Additionally, he holds a Ph.D. in Physics from the Federal University of Ceará (UFC). He has teaching experience in public high schools and has also served as a professor in Physics undergraduate courses at the Federal University of Ceará.He works on developing programs (Python, C, Octave, R) to solve problems in complex systems, such as traffic flow in cities and data in networks, using statistical mechanics and data treatment (Big Data).

Experience

1. Head of Advanced Analytics Ml

   MJV Technology & Innovation

   Dec 2025 — Present · Rio de Janeiro, BR

   Responsible for leading the strategy and execution of Advanced Analytics and Machine Learning initiatives, with emphasis on scalable architectures and high-performance AI solutions. Activities include designing analytical systems, developing end-to-end ML pipelines, and establishing robust MLOps frameworks to ensure governance, reliability, and seamless integration with enterprise environments.Focus areas include predictive and prescriptive modeling, algorithmic optimization, intelligent automation, and the application of state-of-the-art AI techniques to support high-impact decision-making. The role also encompasses managing multidisciplinary teams, enforcing engineering best practices, and implementing standards for versioning, monitoring, and model operationalization.Work is centered on combining applied research, data engineering, and machine learning to elevate analytics maturity and deliver measurable business value.

Education

• Federal University of Ceara

  Doctor of Philosophy - PhD, Physics - Complex Systems

• Federal University of Ceara

  Master's in Physics, Physics of Condensed Matter and Materials

  2013 — 2015

• Federal University of Ceara

  Graduação, Licenciatura em Física

• Universidade de Coimbra

  Graduação, Física

  2010 — 2012