Anirudh Tallury
ETL Development | Data Warehousing | AWS Redshift | Python | Optimized data pipeline, reducing latency by 30%
- Role
- Data Analyst at Johnson & Johnson
- Location
- Burlington, MA, US
- LinkedIn followers
- 500 followers
About Anirudh Tallury
Experienced Data Analyst with around 3+ years in healthcare and finance industries…
Experience
Data Analyst
Aug 2024 — Present · US
Delivered a predictive analytics initiative using R, SQL, and Snowflake to model patient risk trajectories across chronic conditions, enhancing resource allocation and care stratification across 40+ facilities in alignment with value-based care objectives. • Developed anomaly detection pipelines using PySpark and MLflow to monitor abnormal utilization patterns in outpatient data; accelerated intervention timelines and prevented overutilization incidents, saving $800K in unnecessary treatment costs annually. • Orchestrated cloud-native ETL workflows on Azure Data Factory to integrate lab results, vitals, and imaging records; increased refresh frequency from weekly to daily and ensured high-fidelity ingestion of structured and unstructured health data. • Constructed compliance dashboards using Tableau to monitor CMS quality metrics and readmission benchmarks; empowered leadership with real-time visibility into program gaps, achieving 100% reporting adherence for three consecutive quarters. • Automated payer contract validation audits using SSIS and Redshift, surfacing discrepancies between reimbursement rates and payment terms; enabled resolution of claims underpayment issues worth $2.5M over one fiscal year. • Analyzed EHR usability by mining user-interaction logs via MongoDB, identifying physician workflow pain points and reducing charting time by 17% through streamlined UI enhancements and form redesigns. • Visualized patient journeys using Matplotlib and Seaborn to highlight diagnostic delays and care handoff issues; supported care redesign efforts that reduced diagnosis-to-treatment lag by 22% for oncology services. • Collaborated with medical directors, actuaries, and informatics specialists to co-design intervention strategies backed by stratified outcomes analysis, driving a 9% improvement in chronic condition control rates and boosting quality incentive attainment.
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