Avinash Nagabelly

Data Engineer

Tempus

Sep 2024 - Current (2 years 2 months)

Applied advanced ML techniques (Regression, Classification) and NLP using Hugging Face on around 20,000 patient records, forecasting enrollment trends and identifying critical high-risk patients, optimizing staffing across 3 clinical sites. Developed ETL pipelines using dbt, Docker, Kubernetes, and AWS S3, processing over 10,000 clinical trial records weekly, improving data ingestion efficiency by 14% and enabling faster trial reporting. Automated data processing workflows using AWS Glue, integrating multiple clinical datasets and reducing manual intervention by 20 hours weekly, improving trial data availability for analytics. Engineered data models in Snowflake and PostgreSQL for about 5 million patient records, reducing report generation

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Data Engineer Intern

IQVIA Holdings Inc.

May 2024 - Aug 2024 (4 months)

Assisted in designing ETL workflows using Python and Apache Airflow, processing around 5,000 clinical records daily, ensuring timely, accurate data availability for downstream analytics and trial monitoring. Cleaned and validated clinical trial datasets using Plotly and Matplotlib, correcting inconsistencies across 50+ tables, improving data accuracy by 8% and supporting reporting for trial managers. Supported data modeling and transformation using dbt, preparing structured datasets for analytics, enabling trial teams to monitor patient enrollment trends efficiently and reduce manual reporting effort.

Data Analyst

PhonePe

Jun 2021 - Jun 2022 (1 year 1 month)

Processed around 1 million transaction records using SQL and MySQL, improving reporting accuracy by 12%, preventing 1,200 failed transactions monthly, and helping retain approximately $50K monthly, reducing payment losses. Built Tableau and Looker dashboards on AWS Redshift with finance and product teams, tracking 100+ metrics, giving visibility into transaction trends, user engagement, and payment success rates, reducing manual reporting by 18%. Developed predictive models with Pandas and Scikit-learn, orchestrated via AWS Lambda, forecasting payment failures and user churn, improving payment success rates by 11%, and enabling timely interventions for high-risk users. Defined KPIs across around 5 business verticals with cross-functional st

Associate Data Analyst

PhonePe

Jun 2020 - May 2021 (1 year)

Assisted in maintaining ETL pipelines using SQL, Amazon RDS, and MongoDB, processing around 200 client files monthly, and improving reporting accuracy for finance and operations teams. Created Excel dashboards with Power Query and Pivot Tables, tracking 25+ KPIs, providing operational insights to business units and reducing manual reporting efforts by 13%, enhancing reporting consistency. Performed basic data processing using Python and NumPy, cleaning and formatting datasets to help senior analysts optimize reports, maintain data quality, and ensure consistent insights for decision-making. Validated and cleaned over 100K client records weekly, minimizing errors by 12%, ensuring reliable data for cross-functional teams, supporting complianc

Avinash Nagabelly

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Avinash Nagabelly

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