Aditya Nair
@adityanair2
I build reliable multi-cloud data and MLOps pipelines for telecom, healthcare, and financial analytics.
United StatesWhat I'm looking for
At EchoStar, I build Dataiku and Azure DevOps MLOps workflows for telecom telemetry, customer usage, device performance, and operational analytics. I engineered batch and real-time pipelines processing 500K+ daily data points, reducing reconciliation time by 80% and improving query performance by 60%.
Previously at Novartis and Tech Mahindra, I delivered healthcare and financial ETL, feature engineering, data-quality, and reporting workflows across Dataiku DSS, Spark, Snowflake, AWS, Azure, Power BI, and Tableau. I've supported production-ready ML workflows, cloud cost optimization, automated validation, and governed datasets for clinical, commercial, and executive reporting.
Experience
Work history, roles, and key accomplishments
Built end-to-end MLOps workflows for telecom data, reducing manual deployment effort by 50% and improving pipeline stability by 25%. Automated CI/CD processes and implemented monitoring dashboards to enhance reliability and SLA compliance.
Delivered $150K+ in annual cloud cost savings and achieved 99.9% pipeline reliability by building automated Dataiku workflows. Improved predictive model accuracy to 94.6% through feature engineering and supported MLOps delivery across clinical and commercial analytics.
Boosted query performance by 35% on financial datasets by architecting star-schema data warehouses. Reduced reporting errors by 40% and cut deployment times by 40% through automated ETL pipelines and Dockerized CI/CD.
Education
Degrees, certifications, and relevant coursework
Lewis University
Master of Science, Data Science
2022 - 2024
Master of Science in Data Science from Lewis University from 2022 to 2024.
Tech stack
Software and tools used professionally
Availability
Location
United StatesAuthorized to work in
Job categories
Skills
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