I'm a Data Scientist building data infrastructure at scale. I focus on platform architecture and cloud optimization to turn raw data into insights.

I love solving complex problems at the intersection of data engineering, optimization, and infrastructure. Whether it's scaling analytics pipelines to billions of events or reducing compute costs, I'm interested in the hard problems.

• Current: Data Scientist @ Fanatics 📊

• Education: Management Engineering + Computing @ University of Waterloo 🎓

• Previously: Snapchat, Amazon, Intact, Manulife 🏆

Languages: Python, SQL, R, Java

Data & Cloud Engineering:

• Data Warehousing: Snowflake, BigQuery, Redshift
• Orchestration & Pipelines: Dagster, Airflow, dbt
• Cloud Platforms: AWS (S3, Redshift, Glue, Athena, QuickSight), GCP, Azure
• Distributed Systems: Spark, Kubernetes

Specialties: ETL Pipeline Design, Real-time Analytics, Data Warehouse Architecture

Tools & Libraries: Pandas, NumPy, Scikit-learn, XGBoost, TensorFlow, Spark SQL, Tableau, Streamlit, Plotly, Docker, Git, Jupyter

🔍 Infrastructure optimization & scheduling algorithms
📈 Real-time data systems & streaming architectures
🌱 Problems at scale (billions of events, petabyte datasets)

• 📧 Email: aashan5050@gmail.com
• 💼 LinkedIn: @aashanm