Design and implement data validation pipelines and model evaluation workflows in a cloud environment (AWS).
Integrate data and evaluation metrics into an automated, auditable pipeline.
Modularize the pipeline to facilitate reuse, testing, and maintenance.
Collaborate with Data Science, Data Engineering, and Product teams.
Ensure best practices for versioning, logging, monitoring, and automated testing.
Propose continuous improvements to data architecture and validation processes.

Experience with AWS (Glue, S3, SageMaker, Lambda, among others);
Experience in data manipulation and statistical modeling (Python, SQL, PySpark);
Solid experience in data science;
Practical experience with LLMs;
Experience with agile methodologies;

Senior Data Scientist

Key skills