José Luis Cádiz Sejas

Responsible for improving and maintaining a McKinsey-developed recommendation system to optimize plant decision-making. The system runs on Linux, leveraging Kedro for data and model pipelines and Prefect for orchestration. Key responsibilities include:

• Enhancing system functionality and implementing new features.
• Debugging and optimizing performance for reliability and efficiency.
• Overseeing the approval and deployment of recommendations within the expert control system to drive plant optimization.
• Tracking and analyzing the tool’s monetary value contribution.

Developing data analyses and models to understand the dynamics of various stages of the process and their potential impact on recoveries, concentrate grades, and equivalent fine copper, including:

• P80 analysis in milling.
• Enrichment ratio analysis in collective flotation.
• Molybdenum recovery analysis in selective flotation.
  

• Company Overview: 6-month application process, where 7000 people applied
• Only 1% of the applicants were selected, of which only 10 were men
• The internship consists of a program to develop leadership skills in young professionals to later work in supervisory, management and change agent positions
• GSYS - Superintendence of Electricity and Fuel: Implementation of energy management system, maintenance operating system (SOMA), automation and data visualization in Power BI/Python
• GCON - Superintendence of Electrical Maintenance and Automation: Standardization of procedures to improve security at the Chuquicamata concentrator plant
• Operational Excellence: KPI analysis, project planning, automation and data visualization in Power BI/Python
• 6-month application process, where 7000 people applied
• Only 1% of the applicants were selected, of which only 10 were men
• The internship consists of a program to develop leadership skills in young professionals to later work in supervisory, management and change agent positions

• Data Engineering with Dagster & containerizing web tools with Docker
• Statistical analysis of restrictions and maintenance in process equipment
• Build predictive and prescriptive models to SAG mills
• MLOps & Data Engineering with Airflow and MySQL
• API with Flask
• Visualization of information with Plotly
• Upskill people with cloud technologies

• Stored Procedures with SQL Server
• API with Flask
• Visualization of information with Plotly
• Build predictive and prescriptive models to SAG mills
• MLOps with Azure Functions

• Formulation of a business model and development of a predictive model for lithium production by recycling batteries