Data Analyst - Healthcare Analytics Expert

Swarna Rekha Komuravelly

Data Analyst

Worcester MA 508-***-**** ***********.***********@*****.*** LinkedIn Professional Summary

Experienced Data Analyst with 4 years of expertise in analyzing complex datasets, uncovering trends, and delivering actionable insights to drive business decisions. Skilled in data visualization, statistical analysis, and predictive modelling, with a proven track record of optimizing processes and improving operational efficiency through data-driven strategies.

• Results-driven Data Analyst with over 4 years of experience transforming clinical and operational data into actionable insights to improve patient outcomes and reduce costs.

• Proficient in Python, SQL, Tableau, Power BI and designing and building ETL pipelines.

• An expert in statistical analysis, machine learning, and data storytelling.

• Specialized in analyzing Electronic Health Records (EHR), claims data, and hospital metrics to support data-informed decision- making across care teams and executive stakeholders.

• Skilled in building end-to-end ETL pipelines, applying SQL, Python, and Power BI/Tableau to cleanse, model, and visualize complex datasets for real-time performance tracking.

• Proven success in reducing 30-day readmission rates, identifying high-risk patients using statistical models (e.g., logistic regression), and optimizing patient care pathways.

• Expertise in healthcare KPIs such as readmission rate, length of stay, cost per episode, and clinical compliance metrics.

• Collaborated with cross-functional teams including clinicians, care coordinators, and IT, ensuring alignment of data strategy with quality improvement goals.

• Proficient in HIPAA-compliant data handling, and well-versed in working with structured/unstructured clinical data, ICD-10 codes, HL7, and FHIR formats.

• Experienced in communicating insights to non-technical stakeholders through storytelling dashboards, executive reports, and stakeholder presentations

• Strong background in predictive analytics, patient risk stratification, and real-world evidence (RWE) generation to support population health initiatives.

• Created interactive dashboards and visualizations for stakeholders using Tableau and Power BI.

• Implemented scalable data workflows and pipelines using Python, SQL, and cloud-native services.

• Engaging with the stakeholders for leadership, feedback loops, providing training and support, monitoring progress.

• Used Power BI for real-time dashboards to tell the story behind each and single change.

• Facilitated cross-functional collaboration with teams across different regions to ensure alignment in change management initiatives.

• Adapted change strategies to fit regional needs, ensuring successful adoption of new processes and technologies across global teams.

• Experienced working across the Software Development Life Cycle (SDLC) using Agile, Scrum, and Waterfall methodologies.

• In collaboration with senior stakeholders and program sponsors, delivered impactful leadership presentations and executive summaries to convey project progress, change adoption metrics, risk assessments, and strategic recommendations.

• Produced visual and engaging PowerPoint presentations for executive audiences, ensuring alignment between project outcomes, business objectives, and organizational KPIs.

• Analysed and synthesized technical insights and platform adoption data into actionable business decisions for quarterly and milestone-based presentations to leadership teams. SKILLS & TECHNOLOGIES

• Analytics Tools: Power BI, Tableau, Excel (PivotTables, VLOOKUP)

• Programming Tools: Python (Pandas, Numpy, Scikit-learn)

• Databases & ETL: SQL, ETL Pipelines (Python, SQL)

• Healthcare Knowledge: EHR, Claims Data, HIPAA, Readmission Metrics

• Modelling & Statistics: Logistic Regression, Risk Scoring, A/B Testing, Hypothesis Testing

• Communication: Dashboarding, Stakeholder Reports, Storytelling with Data

• Methods: Agile, Scrum, Change Management (ADKAR) Professional Experience

Healthcare Data Analyst Scholar IT Texas Feb 2025 – Present

• Analysed 3 years of hospital readmission data using SQL and Python to identify high-risk diagnosis groups and patient profiles, improving care coordination strategies.

• Developed a logistic regression model to predict 30-day readmission risk based on comorbidities, discharge type, and length of stay.

• Built and deployed a Power BI dashboard visualizing real-time KPIs such as readmission rates by condition, physician, and department for hospital leadership.

• Collaborated with clinicians to design data-driven discharge planning interventions, resulting in a 12% drop-in readmission rates over a 6-month period.

• Presented insights to stakeholders using PowerPoint and data storytelling, enabling executive decisions that supported compliance and cost reduction goals.

• Engineered an end-to-end ETL pipeline using Python and SQL to extract, transform, and load patient data from EHR systems, ensuring high data quality and consistent refresh cycles for dashboard updates.

• Conducted cohort and root cause analysis to isolate top 5 diagnosis-related groups (DRGs) contributing to 70% of readmissions, guiding clinical teams in prioritizing intervention strategies. Tech Stack: Python, SQL, Power BI, Pandas, NumPy, Scikit-learn, Excel, PowerPoint, Jupyter Data Analyst Clark University Massachusetts Jan 2024 -Dec 2024

• Designed and developed interactive Power BI dashboards to showcase key performance indicators (KPIs), effectively responding to client requirements.

• Analysed HR data to examine gender-related KPIs, identifying root causes of gender balance issues at the executive management level, and providing actionable recommendations.

• Strengthened Power BI skills to address clients' data visualization needs, delivering effective and tailored solutions.

• Demonstrated strong communication skills by crafting concise and informative email summaries for engagement partners, delivering insights and actionable suggestions.

• Leveraged analytical problem-solving skills to support data-driven decision-making, showcasing a commitment to addressing business challenges with data insights.

Tech Stack: Power BI, DAX, SQL, Excel, Python (Pandas), Jupyter, KPI analysis, HR analytics Real- Time Analytics Developer – Network Monitoring Accenture Hyderabad, India Sep 2022 – Jun 2023

• Analysed real-time network performance metrics and customer usage data to assess service quality and detect anomalies such as dropped calls, data lags, and latency spikes using SQL and Python.

• Developed interactive Tableau dashboards for operations teams to monitor KPIs such as call success rate, data throughput, customer churn risk, and region-wise service availability.

• Built automated reports and alerting systems to track SLA violations and key metrics (e.g., average call duration, jitter, bandwidth utilization), shared daily with compliance and engineering leads.

• Conducted root-cause analysis of network congestion events, identifying performance bottlenecks by cell tower, region, and time of day.

• Supported marketing and pricing teams with on-demand analytics to evaluate the effectiveness of new plan rollouts, bundling offers, and customer upgrade behavior across geographies. Tech Stack: SQL, Python, Tableau, KPI monitoring, SLA tracking, network performance analysis, customer churn modelling Data Analyst Innomatics Research Labs Hyderabad, India Jan 2022 – Aug 2022

• Conducted web scraping using Python libraries like BeautifulSoup and Requests to extract and analyze basketball data from external websites.

• Cleaned and pre-processed raw datasets, handling null values and irrelevant features, resulting in a structured data frame for analysis.

• Performed exploratory data analysis (EDA), including univariate, bivariate, and multivariate analysis, to uncover trends and insights.

• Created data visualizations using Matplotlib and Seaborn, such as bar plots, scatter plots, and pie charts, to present findings effectively.

• Conducted correlation analysis to identify key performance indicators for creating an optimal basketball team.

• Delivered actionable insights, such as identifying top-performing players (e.g., James Harden) and analyzing team compositions based on player age and position.

• Presented results through clear and concise reports, including statistical summaries and visual representations. Tech Stack: Python, BeautifulSoup, Requests, Pandas, Matplotlib, Seaborn, data cleaning, web scraping, exploratory data analysis (EDA), data visualization

Projects:

NLP Chatbot with Retrieval Augmented Generation (RAG) – Kanji Chatbot

• Tech Stack: Python, LangChain, HuggingFace, Streamlit, ChromaDB, Ollama

• Developed a domain-specific contextual chatbot using Retrieval Augmented Generation (RAG) architecture, powered by open- source LLMs (Gemma 2B via Ollama) and LangChain framework.

• Engineered a complete data ingestion pipeline: uploaded PDFs, split into text chunks, generated embeddings, and stored them in ChromaDB for contextual retrieval.

• Implemented a Q&A chatbot interface in Streamlit, enabling real-time question answering based on uploaded content, maintaining chat history and user context.

• Enabled smart document search and response generation by combining vector similarity search with LLM response generation, improving relevance and accuracy.

• Integrated libraries and loaders for diverse file types and content sources including PDFs, Arxiv, Wikipedia, and HTML pages.

• Focused on low-latency inference using lightweight models for efficient deployment on local machines with limited resources.

• Prioritized ethical considerations and user experience, designing a secure, English-language-only conversational interface. IMDB Movie Analysis Dashboard using Splunk (NLP Project)

• Tech Stack: Splunk, SPL, IMDB Dataset, CSV, Data Visualization

• Parsed and indexed IMDB movie data into Splunk for real-time log analysis and interactive querying.

• Developed SPL-based queries to analyze genres, votes, content ratings, and yearly trends.

• Built interactive dashboards showcasing top-rated genres, highest vote counts, and severity of content (Mild, Moderate, Severe).

• Visualized trends in movie releases over time using bar charts and time-series panels.

• Filtered and compared data across key genres like Comedy, Drama, and Animation for stakeholder reporting.

• Gained hands-on experience in text-based analytics using real-world media data.

• Strengthened understanding of content analytics, user preference patterns, and dashboard storytelling. Education

Masters of Science in Data Analytics

Clark University, Worcester, MA

Certifications

• Advanced certificate programme in Data Science, IIIT-B

• Data Analytics & Power BI Virtual Experience Program

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