Development and implementation of machine learning algorithms in an agile environment, following MLOps best practices in both databricks and AWS platforms.- Used python (Pyspark, Pandas, Shap, Sklearn, Pytorch) and SQL to create predictive company resource allocation systems.- PEP8 coding standards and best data science practices applied to modular software. - CI/CD git development in bitbucket, working with a team of five amazing machine learning engineers, data engineers, data analysts and data scientists.- Stakeholder technical and non-technical presentations. Clear communication and time management.- Built internal project dashboards and software diagrams.- Side project: global networking platform, helping internal employees reach out and get paired to have catch ups with other departments within the company.

Design and development of tools, processes/systems, data visualizations, and data automations for the European business within the Asset Productivity Department at CHEP.- Power Bi (DAX)- Power Query (M)- Power Automate- Power Apps & Sharepoint- Python- SQL (AWS Athena)- VBA

- Use of SAP, VBA and BW.- Power BI Supply Chain Tools Development.- Adjust of flows and production at plant level.- Manage plant level inventories (All Europe).- Execution and forecasting of the seasonal supply surge.- Quality system management.- Audits and incidences analysis. BI, DAX and Power Query.

CNN, ViT and traditional machine learning classification algorithms applications to land coverage.- Custom research python ML library development in visual studio, following MLOps and PEP8 standards.- Earth Engine for developers console.- GeoPandas, Pytorch, Fastai, Pandas, Numpy.- Model visualisation deployment with streamlit. Model tracking with mlflow.- GIS analysis and inventory planning and sampling with ArcGIS.