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Sahithya Gangarapu

@sahithyagangarapu

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Data Analyst turning healthcare data into actionable insights with BI and ML.

United States

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What I'm looking for

I’m looking for a data analytics role where I can build HIPAA-compliant ETL, develop predictive models, and deliver KPI dashboards that improve operational efficiency and decision-making with cross-functional teams.

I’m a Data Analyst with 3+ years of experience across healthcare and consulting, turning complex datasets into actionable insights. I leverage SQL, Python, and BI tools (Tableau/Power BI/Excel) to build predictive models, track KPIs, and develop dashboards that directly improve operational efficiency.

In my current Tenet Healthcare role, I’ve engineered predictive patient readmission models, delivered interactive Tableau dashboards for departmental KPI tracking, and implemented HIPAA-compliant ETL pipelines with AWS Glue for weekly processing of clinical records. Previously at Deloitte, I applied regression/classification modeling, automated reporting workflows, and built ETL pipelines with Azure Data Factory and Apache Spark—consistently reducing delays, reprocessing costs, and manual errors through measurable analytics impact.

Experience

Work history, roles, and key accomplishments

Current

Data Analyst

Current

Tenet Healthcare

Jul 2024 - Present (1 year 10 months)

Engineered predictive patient readmission models using Python, pandas, and NumPy on EMR data, reducing readmissions for 3,000+ high-risk patients across 5 hospitals. Built HIPAA-compliant AWS Glue ETL pipelines and Tableau dashboards, increasing throughput by 120+ patients/month and improving reporting accuracy by 13%.

Python SQL Tableau AWS Glue AWS RedShift EMR Data Analysis HIPAA compliance predictive modeling Data Wrangling

Data Analyst

Deloitte

Jan 2022 - Nov 2022 (10 months)

Applied regression and classification modeling with scikit-learn on operational datasets, uncovering patterns that reduced processing delays by 25,000+ claims per quarter. Developed Power BI KPI dashboards and Azure ETL/A-B testing pipelines, accelerating monthly reporting by 14% and reducing claim reprocessing/manual error costs by $150K annually.

Python SQL Power BI scikit learn Azure Data Factory A B Testing Apache Spark Data Modeling

Reporting Analyst

Deloitte

Jan 2021 - Dec 2021 (11 months)

Built Excel and Power BI dashboards and KPI summaries, streamlining reporting workflows and saving ~$75K annually in third-party analytics costs. Cleaned and analyzed 50,000+ records/month with Python/pandas and delivered high-risk patient reporting, improving reporting accuracy by 11% and reducing turnaround time by 17%.