Data Analyst Power Bi

Shirisha Hechirla

Data Analyst

Austin, TX (Open to Relocate) +1-850-***-**** ****************@*****.*** LinkedIn Professional Summary

Data Analyst with 3+ years of experience in healthcare and financial analytics. Proficient in data wrangling, SQL scripting, statistical analysis, predictive modeling, and data visualization. Skilled in ETL processes, data modeling, and developing reusable analytics pipelines. Experienced with schema design, security compliance (HIPAA, CMS standards), and Agile collaboration. Committed to delivering insightful data solutions through automation, version control, and CI/CD practices.

Technical Skills

Programming & Scripting: Python (Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn), SAS, R, SQL, VBA Testing & CI/CD: Unit Testing (pytest), Automated Performance Testing, GitHub Actions, Reusable Code Libraries Data Visualization & BI: Tableau, Power BI, Looker, Excel (PivotTables, Charts, Advanced Functions, Macros), LookML Statistical Analysis & Modeling: EDA, A/B Testing, Hypothesis Testing, Regression, Predictive Modeling, Time-Series Forecasting, Data Analysis Databases & Modeling: Microsoft SQL Server, MySQL, PostgreSQL, Oracle, BigQuery, MongoDB, Dimensional Modeling, Schema Design Data Engineering & ETL: ETL Pipelines, Data Wrangling, Data Transformation, API Integration, Server-side Logic Cloud & Big Data: AWS (S3, Redshift), Google BigQuery, Azure Data Studio, Snowflake, Databricks Tools & Platforms: Jupyter Notebook, Anaconda, Git/GitHub, Alteryx, Google Sheets, Google Analytics, SAP, ETRM Systems, ERP Systems, Microsoft Word, PowerPoint

Project Management: JIRA, Asana, Confluence

Soft Skills: Cross-functional Communication, Agile/Scrum, Problem Solving, Stakeholder Reporting, Documentation Professional Experience

UnitedHealth Group – Data Analyst

Florida, USA Dec 2024 – Present

• Analyzed over 2 million healthcare claims using SQL Server and Python, identifying billing discrepancies and reducing reporting delays by 18%.

• Created Tableau dashboards to monitor patient treatment journeys across 50+ hospitals, enhancing executive-level decision-making.

• Developed a logistic regression model for predicting patient readmission risk, improving early detection accuracy by 22%.

• Built data quality pipelines integrating 5+ data sources, reducing data preprocessing time by 35%.

• Designed relational database schemas to standardize data ingestion and transformation processes.

• Implemented HIPAA-compliant data anonymization and RBAC, successfully meeting CMS audit requirements.

• Wrote unit tests using pytest to validate pipeline integrity, reducing production bugs and ensuring data reliability.

• Created reusable Python modules and workflow templates to streamline analytics processes.

• Participated in Agile sprint planning alongside engineers, PMs, and clinicians to ensure on-time delivery.

• Used GitHub and GitHub Actions for version control and automated CI/CD pipeline deployment. Mphasis – Data Analyst

Hyderabad, India Jan 2022 – May 2024

• Developed complex SQL Server queries and stored procedures to automate monthly reporting for 3 financial units.

• Designed Power BI dashboards to track logistics KPIs, improving on-time delivery rates by 12%.

• Conducted A/B testing and funnel analysis, increasing user retention by 9.5% and extending average session time by 11%.

• Built time-series forecasting models (ARIMA, ETS), enhancing sales trend predictions with a 17% accuracy improvement.

• Automated weekly data workflows in Python, using pandas and openpyxl to reduce manual effort.

• Collaborated on dimensional data modeling projects to optimize database schemas for reporting efficiency.

• Investigated recurring transaction anomalies, identifying and resolving root-cause issues in data transformation logic.

• Authored internal documentation and dashboard templates for scalable deployment across multiple client projects.

• Created visual decks and reports for both technical and non-technical stakeholders, improving communication and transparency. Projects

PhishGuard AI – SMS Phishing Detection Tool (Python, Streamlit, TF-IDF, Logistic Regression)

• Developed an SMS phishing detection web application with 85% model accuracy and real-time feedback functionality.

• Implemented a reusable text vectorization and classification pipeline, reducing false positive rates by 10%.

• Created unit tests to validate model predictions and prevent inference errors. Image Segmentation for Multiple Myeloma Cell Detection (PyTorch, U-Net, OpenCV)

• Trained a U-Net convolutional neural network (CNN) to detect plasma cells in microscopy images with 92.4% accuracy.

• Applied data augmentation and architectural optimizations, reducing processing time by 15%. Red Wine Quality Analysis Using Physicochemical Features (Scikit-learn, Pandas, NumPy)

• Performed regression modeling and exploratory data analysis (EDA) to identify key factors influencing wine quality.

• Achieved an adjusted R of 72.5% using multiple linear regression. Education

Florida State University, Tallahassee, FL

Master of Science in Data Science

Gokaraju Rangaraju Institute of Engineering and Technology, Hyderabad, India Bachelor of Technology in Electronics and Communication Engineering Certifications

• AWS Academy Graduate – Machine Learning

• AWS Academy Graduate – Cloud Foundations

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