Data Analytics Engineer for Healthcare and Retail

SOWJANYA PALAKURLA

+1-774-***-**** ********.**.***@*****.*** www.linkedin.com/in/sowjanyapalakurla Worcester, MA, USA PROFESSIONAL SUMMARY

Data Analyst with 3+ years of experience delivering healthcare and retail analytics across UnitedHealth Group, Humana, and Genpact. Skilled in SQL, Snowflake, Python (Pandas, scikit-learn), Power BI, Tableau, and Salesforce reporting to build scalable datasets, dashboards, and forecasting models. Proven impact improving reporting accuracy, reducing manual effort, optimizing inventory, and driving patient retention through data-driven insights, while ensuring HIPAA-compliant data handling in regulated environments.

TECHNICAL SKILLS

Methodologies Software Development Life Cycle (SDLC), Agile/ Scrum, Waterfall Language & Databases Python, SQL, MSSQL Server, MySQL, SQL Server, PostgreSQL Python Packages Pandas, NumPy, Matplotlib, SciPy, Scikit-Learn, Seaborn, PyTorch. Data Analytics Skills Data Manipulation & Cleaning, Predictive Analysis, Statistical Modelling, EDA, Data Analysis, Hypothesis Testing, ANOVA, Regression Analysis, t-test, chi-squared, A/B Testing. Cloud Docker, Kubernetes, AWS (Redshift, Athena, Glue, PageMaker, S3), Azure (Databricks) Tools Tableau, Power BI (DAX), Excel (Pivot table, VLOOKUP, Power Query, Macros) PROFESSIONAL EXPERIENCE

Data Analyst United Health Group, Remote, USA March 2025 – Present

Queried and extracted 10M+ prescription and retail records from Snowflake using SQL, delivering structured datasets that improved pharmacy reporting accuracy and reduced data prep time by 25%.

Cleaned, validated, and transformed 1M+ patient and claims records using Python (Pandas), cutting data inconsistencies by 30% and improving executive reporting accuracy while ensuring 100% HIPAA compliance.

Conducted exploratory analysis and developed time-series forecasting models in Python (scikit-learn, NumPy), enabling pharmacy operations to anticipate seasonal demand and cut excess inventory by 12%.

Designed and deployed 5+ interactive Power BI dashboards to track prescription volume, claims accuracy, and store KPIs, eliminating 30+ hours/month of manual reporting and improving executive decision-making.

Leveraged CRM data and built Salesforce dashboards/reports to monitor renewals, engagement, and pipeline health, equipping leadership with actionable insights that increased patient retention by 14% across 200+ retail locations.

Partnered with Pharmacy Ops, Finance, and IT stakeholders to gather requirements, document BRDs/FRDs, and translate business needs into SQL data extracts and Power BI reporting solutions, improving KPI alignment.

Led UAT planning and execution by defining test cases, validating dashboard outputs against source systems, and managing change requests; ensured end-to-end traceability, maximized data adoption, and reduced post-release reporting defects

Data Science Intern Humana, USA July 2024 – February 2025

Managed the integration of over 5 million patient records from SQL databases and AWS S3 by setting up automated Python- based data pipelines, significantly decreasing data collection time.

Optimized data reliability by applying thorough validation and cleaning procedures using Pandas and complex Excel functions, ensuring consistency and accuracy in downstream analysis.

Applied regression techniques and machine learning algorithms in Python to refine patient admission rate forecasts by 20%, which boosted hospital resource planning by optimizing staff allocation and reducing wait times.

Assessed insurance claims to identify service redundancies, lowering treatment expenses by 10%, and translated performance metrics into interactive Tableau dashboards that contributed to a 25% rise in timely patient care. Data Analyst Genpact, Bangalore, India March 2022 – July 2023

Extracted and analyzed over 1 million transaction records using SQL to identify purchasing trends, improving sales forecasting accuracy by 15%; maintained 10+ interactive Power BI dashboards with DAX and Power Query to optimize reporting and deliver actionable insights for stakeholders.

Conducted advanced statistical analysis with Python Pandas and SciPy to uncover significant cost-saving opportunities, resulting in a n10% reduction in customer acquisition costs.

Developed and applied robust data cleaning protocols using NumPy and Pandas, significantly improving data quality and ensuring the reliability of downstream analysis.

Designed and optimized 5 complex data models, streamlining analytical workflows and delivering deeper insights into customer behavior and preferences, increasing reporting efficiency, and addressing performance issues.

Implemented predictive models with Scikit-learn and Statistics models, improving inventory level forecasts 20% and reducing stockouts by 15%, which enhanced overall supply chain efficiency. EDUCATION

Master of Science in Information Technology

Clark University, MA, USA August 2023 – May 2025

Bachelors of Engineering in Electronics and Communication Engineering Sri Indu College of Engineering and Technology, Hyderabad August 2019 – June 2023

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