Summary
Samuel Hericlis is a Senior Data Scientist with 7 years of hands-on experience building production-grade ML systems, currently leading AI initiatives at Trillia. He combines deep expertise in predictive modeling, computer vision, anomaly detection and generative AI with robust cloud and big-data engineering across AWS, GCP, Azure and Huawei. At IBM he delivered real-time anomaly detection protecting $10M+ assets, boosted model precision to over 90% and drove data-driven decisions with dashboards that cut decision time by 40%. Skilled in MLOps and deployment (MLflow, Docker, CI/CD, FastAPI), he also architects scalable ETL and streaming pipelines using PySpark, Databricks and Dask. A computer engineering and physics-trained practitioner, he pairs rigorous academic curiosity with practical product impact and a taste for research-informed solutions. Outside work he blends a programmer’s toolkit with eclectic interests—Lo-Fi music, physics and math—that inform a thoughtful, experimental approach to modeling.
7 years of coding experience
5 years of employment as a software developer
bachelor degree, Computer engineering, bachelor degree, Computer engineering at Federal University of Ceara
Licentiate degree, Phisycs, Licentiate degree, Phisycs at Universidade Estadual do Vale do Acaraú
Portuguese, English