Ramon Diaz
Lead AI & Data Systems Engineer
AI and data systems engineer. Seven years leading machine learning, cloud modernization, and enterprise data initiatives.
Experience
Jun 2025 to present
1 year, 4 months
Lead AI & Data Systems Engineer
Employer name to be confirmed
Edmonton, Canada
- Designed and deployed a database analytics assistant powered by an LLM backbone, with custom safeguards and validation layers to ensure data accuracy, consistency, and secure access.
- Built automated analytics pipelines and Power BI dashboards, including a 12-week cash-flow forecasting model that improved financial visibility and operational planning.
- Modernized and engineered data pipelines using AWS cloud services to synchronize critical operational and ERP data with the company's CRM platform in near real time.
Enterprise technology and cloud modernization
- Managed and enhanced the organization's software and ERP ecosystem, ensuring data accuracy, standardized processes, and reliable operational performance across business units.
- Modernized SQL-enabled reporting systems by automating Power BI dashboards, streamlining data pipelines, and integrating ERP, HubSpot, and other business applications.
- Improved system efficiency and governance by developing SOPs, documentation standards, training programs, and troubleshooting frameworks for ERP and reporting tools.
- Optimized data acquisition and maintenance processes by establishing data ownership practices, cleanliness standards, and scalable system workflows.
AI, automation, and data engineering leadership
- Built automated analytics pipelines and Power BI dashboards, including a 12-week cash-flow forecasting model that improved financial visibility and operational planning.
- Designed and deployed a database analytics assistant powered by an LLM backbone, with custom safeguards and validation layers to ensure data accuracy, consistency, and secure access.
- Modernized and engineered data pipelines using AWS cloud services to synchronize critical operational and ERP data with the company's CRM platform in near real time.
- Implemented automation strategies that reduced manual reporting, standardized data flows, and increased efficiency across business units.
Strategic technical leadership and cross-functional delivery
- Partnered with operations and leadership to build a long-term roadmap for AI, automation, and data-driven decision-making aligned with organizational objectives.
- Translated business needs into clear, actionable reporting tools, dashboards, and insights adopted across multiple departments.
- Developed and delivered training programs for new users across all software systems, driving adoption and increasing data literacy organization-wide.
- Collaborated with cross-functional teams to recommend process improvements, streamline system usage, and prioritize high-impact technology initiatives.
Feb 2022 to Jun 2025
3 years, 5 months
Data Scientist
Encona
Edmonton, Canada
- Developed supervised models (e.g., XGBoost, Random Forest) for revenue forecasting and client scoring; applied robust validation techniques (e.g., out-of-time split) to ensure generalization.
- Designed a cost-efficient data infrastructure using Azure Blob, SQL, Linux-based VMs, and Container Jobs to support scalable automation and analytics.
- Designed, deployed, and maintained a Docker-based OpenEdX Learning Management System in Azure, developing both front-end and back-end components while collaborating in an Agile environment with cross-functional teams.
Predictive modeling and data engineering
- Developed supervised models (e.g., XGBoost, Random Forest) for revenue forecasting and client scoring; applied robust validation techniques (e.g., out-of-time split) to ensure generalization.
- Built a robust data pipeline utilizing Azure DevOps, Storage Blobs, and Container Jobs.
- Designed a cost-efficient data infrastructure using Azure Blob, SQL, Linux-based VMs, and Container Jobs to support scalable automation and analytics.
Data infrastructure, analytics, and business intelligence
- Developed scalable data infrastructure in Azure, including virtual machines (Linux OS), blob storage, and MySQL services.
- Automated data extraction from multiple company web service APIs using Python.
- Designed and implemented key performance indicators (KPIs) and multiple Power BI dashboards, providing real-time insights for weekly management meetings.
- Created a customer satisfaction dashboard, integrating data from both NoSQL and MySQL sources, to monitor and improve client feedback metrics.
Machine learning deployment and automation
- Designed, deployed, and maintained a Docker-based OpenEdX Learning Management System in Azure, developing both front-end and back-end components while collaborating in an Agile environment with cross-functional teams.
- Automated manual reporting workflows by integrating ERP data into Power BI dashboards and implementing refresh pipelines using Power Automate and Python, supported by SOPs that standardized reporting and data transformation processes.
- Utilized Git version control and ML workflow best practices to ensure reproducible development, reliable deployment, and continuous improvement of platform features and data-driven solutions.
Sep 2021 to Apr 2024
2 years, 8 months
Computer Science Research Assistant
University of Alberta
Edmonton, Canada
- Developed and deployed machine learning models, including deep learning (CNNs), to predict mental health states such as depression, stress, and anxiety based on activity tracker data and audio signals.
- Developed a novel Resilience to Stress Index (RSI) to measure individuals' resilience based on physiological data (e.g., muscle response and blood volume pulse).
- Developed a data-capturing IoT application in Android Studio to collect smartwatch sensor data and enable real-time mental health monitoring and prediction.
Machine learning for behavioral prediction and signal processing
- Developed and deployed machine learning models, including deep learning (CNNs), to predict mental health states such as depression, stress, and anxiety based on activity tracker data and audio signals.
- Cleaned, preprocessed, and transformed sensor data for use in machine learning models, ensuring quality inputs for predictive accuracy.
- Implemented time-series models (e.g., VAR, ARIMA, Recurrent Neural Networks) to analyze mood trends and predict behavioral patterns with successful outcomes.
Algorithm development and unsupervised learning techniques
- Developed a novel Resilience to Stress Index (RSI) to measure individuals' resilience based on physiological data (e.g., muscle response and blood volume pulse).
- Applied unsupervised machine learning techniques (e.g., PCA, Kernel PCA, Mahalanobis Distance, Cluster Validity Index) to compute RSI by analyzing inter-cluster distances in biofeedback data from 71 participants.
End-to-end data solutions for health analytics
- Developed a data-capturing IoT application in Android Studio to collect smartwatch sensor data and enable real-time mental health monitoring and prediction.
- Designed and implemented data pipelines to collect and process large volumes of sensor and biofeedback data for machine learning analysis.
Aug 2019 to Jun 2021
1 year, 11 months
M.S., Computer Science
Tecnologico de Monterrey
Mexico
High-Performance Alumni 100% Scholarship for the master's degree
Jun 2016 to Jul 2019
3 years, 2 months
Purchases Analyst
Nissan Motors
Toluca, Mexico
- Created data analytics projects for exchange rate prediction and analysis of foreign currencies, supporting strategic decision-making in procurement and pricing.
- Managed new product technology implementations, supplier qualifications, and contract negotiations, ensuring optimal procurement, on-time project delivery, and improved supplier performance.
- Conducted correlation analysis by analyzing and visualizing raw materials price fluctuations, identifying key patterns and trends impacting business operations.
Data-driven analysis and insights
- Created data analytics projects for exchange rate prediction and analysis of foreign currencies, supporting strategic decision-making in procurement and pricing.
- Conducted correlation analysis by analyzing and visualizing raw materials price fluctuations, identifying key patterns and trends impacting business operations.
- Developed actionable insights by integrating data analytics into business operations to support pricing strategies and cost-management initiatives.
Project management and supplier coordination
- Managed new product technology implementations, supplier qualifications, and contract negotiations, ensuring optimal procurement, on-time project delivery, and improved supplier performance.
- Coordinated with suppliers and customers to resolve delivery issues and organized cost-reduction activities, enhancing supply chain efficiency and reducing operational costs.
Six peer-reviewed publications
Projects
A conversational AI chatbot powered by Rasa for dialogue management and Meta's LLaMA for natural language responses.
RPA-Powered Power BI Dashboards
Automated KPI dashboards using Python, Power Automate, and Azure Cloud Services to ingest ERP data and reduce update time by 90%.
ML Twitter Sentiment Analysis Pipeline (Streambit)2020
A full-stack ML pipeline feeding an analytical dashboard that gives companies insight regarding the negative sentiment posted on tweets.
Traffic accident forecasting for Nuevo Leon2020
Followed the CRISP-DM methodology end to end to understand how and where traffic accidents happen in Nuevo Leon and to build a forecasting model.
BasketTracker.AI2020
Monitors and predicts online store prices for essential goods in Mexico: web scraping with Python and Selenium, NLP enrichment with NLTK and scikit-learn, forecasting with Auto ARIMA and Facebook Prophet, and dashboards in Tableau and Amazon QuickSight.
Companies
First company
Founder
One line on what this company does and for whom.
Placeholder: company to be confirmed
Second company
Co-founder
One line on what this company does and for whom.
Placeholder: company to be confirmed
Third company
Founder
One line on what this company does and for whom.
Placeholder: company to be confirmed
Skills and education
Skills
Programming
- Python
- SQL
- C
- JavaScript
Cloud and platforms
- Azure Machine Learning
- Azure Databricks
- Azure Virtual Machines
- Azure Blob Storage
- Azure Key Vault
- Azure SQL
- AWS
- Google Cloud
- Power BI (DAX)
- Linux
- Docker
- Android Studio
- Xcode
Machine learning and AI
- Supervised learning (decision trees, gradient boosting, linear regression, SVM)
- Unsupervised learning (k-means, PCA, density-based clustering)
- Deep learning (LSTMs, CNNs, RNNs, autoencoders, Transformers)
- Natural language processing
- Signal analysis
- Time-series analysis
- LLM-based assistants
- Anomaly detection
Data science
- Data visualization (Matplotlib, seaborn, Power BI)
- Data analysis
- Statistical analysis
Data engineering
- MySQL
- NoSQL
- Hadoop
- Pandas
- PySpark
- API and JSON handling
- ETL pipelines
- Azure DevOps
- SOP automation
- Power Automate
Languages
- Spanish
- English
Education
M.S., Computer Science
B.S., Mechatronics Engineering
Honors and awards
University of Alberta and Tecnologico de Monterrey Seed Grant
Awarded a seed grant to develop his research in mental health using machine learning.
Santander Scholarship with MIT Professional Education, awarded twice
Winner, HackOb 3.0 Confluent Challenge Hackathon
Streambit: a full-stack ML pipeline feeding a dashboard of negative sentiment on Twitter.
Winner, HackMTY Datlas Hackathon
Forecasting traffic accidents in Nuevo Leon, end to end under the CRISP-DM methodology.
High-Performance Alumni 100% Scholarship for the master's degree
Certifications
Machine Learning
Machine Learning: Leveraging Data
Leading the Digital Transformation: From AI and IoT to Cloud, Blockchain, and Cybersecurity