I am a data scientist focused on turning AI and data science research into practical, production-minded insights. I write for analysts, ML practitioners, and builders who want to apply new ideas quickly and responsibly.

What you will get from this blog

• Concise paper breakdowns with practical takeaways
• Implementation trade-offs for real-world systems
• Opinionated perspectives to spark useful discussions

Current focus areas

• Applied GenAI and LLM systems
• MLOps and data platform workflows
• Analytics-to-production decision making

Current stack

ML and data: Dataiku, Airflow, Kafka, Redshift, Hive, Presto, Tableau, Spotfire
Cloud and infrastructure: AWS Bedrock, EKS, S3, Docker, Kubernetes
Engineering and delivery: CI/CD, Selenium, Django, FastAPI, Jira, BitBucket, Artifactory, Spinnaker