📊 Data Engineer | Machine Learning Analyst Diploma | Google Certified Professional Cloud Architect | 🌦 DevOps Enthusiast

Welcome to my GitHub! I'm passionate about exploring technology, especially all things DATA!, Machine Learning, AI, and Cloud Computing.

I'm captivated by ML and AI because their developmental stages mirror the growth of human cognition. Reinforcement Learning reminds me that, like machines, we can learn and grow through experience and feedback.

I'm now stepping into Data Engineering, where I’m excited to strengthen my skills in building data pipelines, structuring information for analytics, and supporting scalable ML systems. I see data engineering as the connective tissue between raw data and meaningful insights, a space where creativity meets engineering.

I also find DevOps fascinating, not just for its technical impact, but for its philosophical reminder: continuous integration and improvement aren’t just for software, they’re essential for becoming better versions of ourselves, iteration by iteration.

• Cloud Computing: AWS, Google Cloud Platform (GCP)
• DevOps Tools: Docker, Kubernetes, Terraform, CI/CD, Vagrant, Maven, Jenkins in-TRAINING!
• Data & Machine Learning: Python, SQL, Pandas, PyTorch, Scikit-learn
• Web Development: HTML, CSS, JavaScript (very basic knowledge)

Tools: Python, Dash, pandas, scikit-learn, seaborn, Plotly, statsmodels, Jupyter, Git, HTML/CSS

• Developed predictive ML models to quantify efficiency and downtime across fuel transaction types using Random Forest, Gradient Boosting, Linear Regression, and a custom PyTorch neural network (R² = 0.98). (Likely overfitting, but this is part of my learning curve =), so I own this!)
• Engineered 30+ features from ~1M transactions and weather logs, including temperature bins, flow rate targets, and seasonal product sensitivity.
• Conducted hypothesis testing (ANOVA, t-tests) and SHAP interpretability to uncover seasonal-product interactions and key environmental drivers (temp, pressure, humidity).
• Deployed a local app and interactive dashboard (Dash, Plotly, Flask) and integrated MLflow tracking for versioning and auditability.

Tools: Python (pandas, geopandas, scikit-learn, seaborn, scipy), Time Series Analysis

• Cleaned and transformed 700K+ environmental records from Canada’s National Pollutant Release Inventory (NPRI).
• Resolved complex location issues using reverse geocoding to infer missing city data, with fallbacks to provincial capitals.
• Engineered time-series features to model 5-year emission growth/decline trends across industries.
• Built and evaluated Random Forest and Linear Regression models (R², MAE, MSE).
• Visualized pollutant trends, residuals, and geographic emission patterns for interpretability and validation.

Tools: AWS, CloudFormation, CI/CD, EC2, S3, CloudFront, VPC, IAM

• Designed and deployed a scalable Instagram-like application prototype using CloudFormation with auto-scaling EC2 instances behind an Application Load Balancer.
• Configured S3 and CloudFront for efficient static content delivery, improving load times and scalability.
• Implemented role-based IAM access controls and secured the environment networking via VPC, NAT gateways, and security groups.

Tools: Flask, PostgreSQL, Docker, Kubernetes, EKS, ECR, CodeBuild, CloudWatch

• Built and containerized a Flask analytics API; deployed on AWS EKS with public access via LoadBalancer.
• Automated builds and Docker image pushes to ECR using AWS CodeBuild.
• Secured deployments using Kubernetes ConfigMaps, Secrets, and liveness/readiness probes.
• Enabled real-time monitoring through CloudWatch Container Insights.

• AI Programming with Python – Udacity AWS AI & ML Scholarship Recipient
• Google Certified Professional Cloud Architect - Dec. 2024 - Dec 2026

• I’m originally from Guadalajara, Jalisco, Mexico, and I’m now a Canadian citizen. 🇲🇽 → 🇨🇦
• My personality type is INFJ-T (Advocate), and I love helping others while solving complex problems!
• I earned my Bachelor’s degree in Biopharmaceutical Chemistry from the University of Guadalajara. Since my degree isn’t recognized in Canada, I decided to shift into computer science, applying my analytical skills to build a new career in tech.

Use AI as you wish to be treated.
Let’s make this a guiding principle in our tech community — to build and use AI with care, for good, and for the greater good.

As Immanuel Kant taught:

“Act only according to that maxim whereby you can at the same time will that it should become a universal law.”

• LinkedIn: linkedin.com/in/almasoria

🚀 Let’s connect and collaborate! I’m always excited to meet like-minded people in tech and work on new challenges together.