Healthcare Data Analyst (SQL, Python, Tableau)

Manikanta Peddiboyina Data Analsyt

Location: NJ Phone: +1-551-***-**** Email: **********************@*****.*** LinkedIn GitHub SUMMARY:

Healthcare Data Analyst with 3.5+ years of experience analyzing clinical, claims, and pharmaceutical datasets to support data- driven decision-making. Strong expertise in SQL, Python, R, and Tableau for data extraction, transformation, validation, and visualization. Experienced in ETL workflows, KPI reporting, healthcare compliance (HIPAA, CLIA, 21 CFR Part 11), and cross- functional collaboration with clinical, operations, and regulatory teams. Proven ability to improve reporting efficiency, optimize data quality, and deliver actionable insights within healthcare and pharmaceutical environments. EDUCATION:

MS in Data Analytics May 2024

Sacred Heart University, CT, USA

B.Tech, Electronics & Communication Engineering June 2021 Presidency University, KA, India

TECHNICAL SKILLS:

Programming & Query Languages:

Data Analysis & Visualization:

Databases:

ETL & Data Processing:

SQL, Python (Pandas, NumPy), R, Excel (Advanced), VBA Tableau, Power BI, Data Modeling, Data Cleaning, Data Validation, Exploratory Data Analysis (EDA), KPI Reporting, Statistical Analysis, Predictive Modeling MySQL, PostgreSQL, Oracle, MongoDB

AWS (S3, RDS, Lambda), ETL Pipelines, Data Transformation, Data Migration, Data Quality Audits

Healthcare & Compliance: HIPAA, CLIA, 21 CFR Part 11, Healthcare Data Governance, PHI Protection Tools & Methodologies: Agile (Scrum), SDLC, JIRA, Git, CI/CD, Root Cause Analysis Statistical & Predictive Modeling: Regression Analysis, Hypothesis Testing, Time Series Analysis, Risk Scoring Models EXPERIENCE:

CRM Data Analyst May 2024 – Current

Pfizer, USA

• Analyzed large-scale pharmaceutical CRM and patient engagement datasets using SQL and Python to identify trends and improve campaign effectiveness.

• Developed automated ETL workflows using AWS (S3, Lambda, RDS) to process structured and semi-structured healthcare data.

• Designed interactive dashboards in Tableau to track KPIs including prescription trends, regional performance, and patient outreach metrics.

• Performed data validation, reconciliation, and quality audits to ensure compliance with HIPAA, internal governance standards.

• Partnered with business stakeholders and clinical teams to translate requirements into actionable analytical reports.

• Improved reporting turnaround time by 30% through automation and query optimization. Data Analsyt Sep 2021 – Dec 2022

Accenture, India

• Performed SQL-based analysis on healthcare claims and patient datasets to identify inefficiencies and improve claims processing throughput by 45%.

• Developed dashboards using Tableau and Excel to visualize clinical operations and financial performance metrics.

• Automated data extraction and transformation processes using Python (Pandas, NumPy) to streamline reporting workflows.

• Optimized Oracle and PostgreSQL queries, reducing reporting latency by 25%.

• Conducted data quality checks and validation processes to ensure regulatory compliance under HIPAA and CLIA standards.

• Collaborated with cross-functional healthcare IT and operations teams to support data-driven improvements. Junior Data Analyst Jun 2021 - Aug 2021

MindTree, India

• Conducted exploratory data analysis (EDA) on patient scheduling, billing, and clinical datasets to identify operational bottlenecks and improve reporting accuracy.

• Assisted in building ETL pipelines for structured and unstructured healthcare data processing, ensuring timely data availability while maintaining healthcare data integrity, privacy protection, and HIPAA-aligned compliance standards.

• Supported dashboard development for operational reporting, KPI performance tracking using Excel, SQL-based reporting tools.

• Performed root cause analysis on data discrepancies across patient billing and claims datasets, improving data accuracy and reducing reporting inconsistencies by 15%.

Projects:

Heart health data analysis

Tech Stack - R, Python, Logistic Regression, MySQL

• Developed a logistic regression model using R and Python to predict heart disease risk from clinical datasets, performed data cleaning and feature engineering, and evaluated model performance using accuracy, precision, and recall to support preventive healthcare decision-making.

Beneficiary Retention Analysis

Tech Stack - Python (Numpy, Pandas), SQL, Excel, Tableau

• Analyzed healthcare beneficiary data using SQL and Python (Pandas, NumPy) to identify churn patterns, built interactive Tableau dashboards to visualize retention trends, and delivered data-driven recommendations to improve patient engagement and retention outcomes.

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