Data Analyst Power Bi

Nitesh Runku Data Analyst

******@***********.*** 940-***-**** USA LinkedIn

Summary

Analytical and detail-oriented Data Analyst with 3+ years of experience leveraging SQL, Python, R, and cloud platforms (AWS, Azure) to transform complex healthcare datasets into actionable insights. Skilled in building automated ETL pipelines, performing advanced statistical analysis, and developing interactive dashboards in Power BI and Tableau. Strong collaborator experienced in Agile environments, with a focus on improving operational efficiency and delivering measurable business value. Technical skills

Programming & Query Languages: SQL (AWS Athena, Azure Synapse Analytics), Python (NumPy, pandas, SciPy, statsmodels), R (ARIMA)

Cloud & ETL Tools: AWS Glue, AWS Athena, Azure Data Factory

Data Visualization: Power BI (DAX, KPIs, slicers, drill-through), Tableau (LOD calculations, dynamic filters)

Data Analysis: Statistical analysis (correlation, survival analysis, cluster analysis, Z-score, IQR), hypothesis testing, time series forecasting

Databases & Data Formats: Electronic Health Records (EHR), claims data (JSON, CSV)

Methodologies: Agile sprint collaboration, requirement gathering, data validation, anomaly detection, ETL optimization Professional Experience

Data Analyst, UnitedHealth Group 10/2024 – Present Remote, USA

Collaborate with clinical teams, product owners, and data engineers in Agile sprints to define requirements, gather patient data needs, and translate them into analytical models that enhance decision-making for clinical outcomes.

Extract, transform, and analyze large-scale healthcare datasets stored in AWS Athena, using advanced SQL techniques such as window functions and CTEs to optimize semi-structured JSON/CSV queries and improve ETL performance.

Conduct in-depth statistical analysis including correlation and survival analysis to identify relationships between treatment protocols and patient recovery patterns, enabling a 15% reduction in readmission rates across multiple demographics.

Design and execute robust data cleansing, aggregation, and hypothesis testing workflows in Python (NumPy, pandas, SciPy, statsmodels), ensuring the reliability of insights before they are shared with stakeholders.

Develop and monitor automated anomaly detection frameworks within AWS Glue and Athena pipelines, improving data validation processes and enhancing clinical dataset accuracy by 10%.

Build and maintain advanced Power BI dashboards with slicers, drill-through capabilities, and KPI metrics using DAX formulas, empowering clinical leadership teams to track patient outcomes, recovery trends, and intervention effectiveness in real time. Data Analyst, The Cigna Group 01/2021 – 12/2023 Andhra Pradesh, India

Gathered requirements with actuarial, provider network, and IT teams to identify opportunities for reducing healthcare costs through claims analysis and process optimization.

Extracted large datasets from Azure Synapse Analytics and developed scalable ETL pipelines using Azure Data Factory, which streamlined integration of claims, provider, and member data, reducing ETL runtime by 30%.

Applied cluster analysis to segment claims data by provider, region, ICD-10 diagnosis codes, and CPT procedure codes, uncovering patterns in high-cost procedures and enabling targeted cost-containment strategies.

Designed statistical models using Z-score and IQR techniques to detect outliers and anomalous claims, significantly reducing fraudulent or erroneous billing and cutting manual review time by 40%.

Developed reusable Python scripts for data preprocessing, feature engineering, and exploratory data analysis, automating repetitive tasks and ensuring data pipelines were reliable for downstream analytics.

Leveraged R to build ARIMA-based time series forecasting models, predicting future high-cost claims with 85% accuracy and providing actuarial teams with proactive cost management insights.

Conducted end-to-end ETL validation and QA checks, achieving 99.5% data accuracy across multiple claim cycles and ensuring compliance with healthcare regulatory standards.

Built Tableau dashboards featuring LOD calculations, dynamic region/diagnosis filters, and provider-level cost simulations, which improved transparency of cost-control initiatives and boosted stakeholder engagement by 50% Education

Master of Science in Health Data Analytics 01/2024 – 05/2025 University of North Texas, Texas, USA

Bachelor of Technology in Mechanical Engineering 06/2016 – 10/2020 Jawaharlal Nehru Technological University, Andhra Pradesh, India

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