Ramya R
Professional Summary
Senior Data Analyst with 5+ years of experience collecting, analyzing, and transforming complex datasets into actionable insights. Expert in SQL and Python, building ETL pipelines and cloud data solutions (Azure, AWS, Snowflake), developing BI dashboards (Power BI, Tableau, Looker) and production-grade ML models (XGBoost, LightGBM, TensorFlow) to support underwriting, claims, and healthcare analytics.
Technical Skills
Work Experience
- Designed and deployed enterprise Power BI dashboards for underwriting and claims analytics (Power BI, DAX, Azure SQL, Snowflake), improving executive decision-making efficiency by 30%.
- Built complex SQL queries, views, and stored procedures to extract and transform large-scale datasets from Azure SQL and Snowflake to support reporting and ML workflows.
- Developed scalable ETL pipelines using Azure Data Factory to automate data integration and orchestration, reducing manual data preparation and handoffs.
- Conducted loss trend and risk analytics using Python (Pandas, NumPy) to identify high-risk claim segments, contributing to a 12% reduction in operational risk exposure.
- Developed and deployed ML models (XGBoost, LightGBM, TensorFlow/Keras) for claim risk prediction and stratification, improving prediction accuracy by 18% over baseline models.
- Implemented data validation and model monitoring frameworks and leveraged Azure ML/cloud services for model training and deployment, improving data accuracy by 25% and tracking performance drift.
- Analyzed large-scale healthcare claims, enrollment, and pharmacy datasets using SQL and Python to identify cost drivers, utilization patterns, and patient outcome trends across 150K+ patient records.
- Designed interactive dashboards in Power BI, Tableau, and Looker (LookML) to track utilization, chronic-condition prevalence, and member engagement for clinical and business stakeholders.
- Built predictive models for patient segmentation and risk scoring to enable early identification of high-risk members and prioritize care management interventions.
- Automated reporting and ETL workflows with Python and Apache Airflow, reducing manual report preparation effort by 30% and improving report reliability.
- Ensured HIPAA and CMS compliance by implementing secure data handling, validation checks, and audit processes; used SAS for claims validation and regulatory reporting.
- Integrated data from APIs, provider feeds, and third-party sources to improve interoperability and translated SQL analyses into executive-level dashboards to inform leadership decisions.
- Developed interactive Power BI and Tableau dashboards to surface KPIs across operations, finance, and customer analytics, enabling data-driven decision-making for client stakeholders.
- Authored complex SQL queries, joins, views, and stored procedures to extract and transform datasets of 5M+ records from SQL Server and Oracle for reporting and analysis.
- Performed data cleaning, transformation, and exploratory data analysis using Python (Pandas, NumPy) to prepare features for forecasting and operational reports.
- Built automated ETL pipelines using SSIS and Azure Data Factory to schedule and orchestrate data flows, reducing manual reporting effort by 35%.
- Assisted cloud migration efforts from on-prem SQL Server to Azure and Snowflake and worked with semi-structured/NoSQL sources (MongoDB, Cassandra) for real-time analytics use cases.
- Collaborated with cross-functional teams in Agile/Scrum, developed data validation frameworks and quality checks that improved reporting accuracy by 20%.
Education
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