Data Analytics Specialist with Healthcare Focus

Akhila Madanapati

Data Analyst

TX, USA +1-551-***-**** *******************@*****.*** LinkedIn SUMMARY

• Data Analyst with 4+ years of experience in healthcare and finance, proficient in Python, SQL, Snowflake, dbt, SSIS, Apache Spark, Alteryx, and Azure Data Factory, delivering scalable and efficient data solutions.

• Built robust ETL pipelines on AWS Glue, Azure Data Factory, Snowflake, and SSIS, integrating structured and semi- structured sources, improving data accuracy, governance, and reliability across enterprise analytics projects.

• Performed EDA, predictive modeling, and advanced analytics using Pandas, NumPy, Scikit-learn, TensorFlow, and R, supporting fraud detection, patient risk scoring, and financial risk analysis with actionable insights.

• Developed real-time dashboards in Power BI, Tableau, Looker, and QlikView, reducing manual reporting by 70% while aligning workflows with HEDIS, CMS, SOX, HIPAA, and financial compliance.

• Collaborated with cross-functional teams using Agile and Waterfall methodologies, gathering BRD/FRD, validating deliverables, and ensuring analytics solutions drove measurable business impact across healthcare and finance domains.

SKILLS

Languages Python, Scala, R, SQL, SAS

Packages / Libraries NumPy, Pandas, Matplotlib, Seaborn, ggplot2, SciPy, Scikit-learn, TensorFlow Visualization Tools Tableau, Power BI, Advanced Excel (Pivot Tables, VLOOKUP) IDEs Visual Studio Code, PyCharm, Jupyter Notebook Database Management MySQL, PostgreSQL, SQL, Oracle, Snowflake, DBT Cloud Technologies AWS, Azure

Methodologies SDLC, Agile, Waterfall, Predictive Modeling Version Control Git, GitHub, Bitbucket

Data Manipulation

Data Analysis, Data Mining, Data Preprocessing, Data Mapping, Data Cleaning, Data Visualization, Data Modeling, Data Warehousing, Data Storytelling, Data Wrangling, Data Acquisition, Data Integration, Data Transformation Other Skills

SSIS, SSRS, Machine Learning Algorithms, CI/CD, Probability Distributions, Confidence Intervals, ANOVA, Association Rules, Clustering, Advanced Analytics, ETL Processes, Informatica, Report Generation, Regression, A/B Testing, Forecasting & Modeling, Hypothesis Testing, Time Series Analysis, Root Cause Analysis WORK EXPERIENCE

Data Analyst McKesson Corporation, USA Aug 2024 –Present

• Built predictive models using Python (Pandas, Scikit-learn) on patient EHR and claims data, enabling early identification of high-risk individuals and improving intervention accuracy by over 30 percent.

• Developed ETL workflows in Alteryx to integrate multi-source healthcare datasets, ensuring consistent data ingestion, transformation, and reliability across clinical, claims, and prescription systems.

• Designed and deployed interactive Power BI dashboards with advanced DAX measures, providing clinicians with actionable insights into patient readmission risks, trends, and cost-saving opportunities in real time.

• Wrote complex SQL queries across SQL Server to extract, validate, and aggregate patient EHR and claims data, enabling accurate datasets that powered predictive modeling and advanced Power BI dashboards.

• Conducted exploratory data analysis, detailed data wrangling, and advanced feature engineering, addressing missing diagnoses, unstructured physician notes, & prescription inconsistencies for reliable predictive modeling outcomes.

• Executed hypothesis testing and A/B testing frameworks to evaluate the effectiveness of new care programs, supporting evidence-based decisions and measurable improvements in hospital readmission reduction initiatives.

• Leveraged Microsoft Azure services, including Data Factory & Synapse, to orchestrate scalable pipelines for healthcare analytics, streamlining data integration while maintaining HIPAA compliance and governance standards.

• Utilized Collibra for metadata management, lineage tracking, and governance, ensuring complete compliance with healthcare regulations, while improving transparency and trust in enterprise data usage across teams.

• Translated complex statistical findings into compelling data storytelling formats, enabling clinical executives to make timely strategic decisions that enhanced patient outcomes and strengthened value-based care delivery models.

• Collaborated with planners and clinical stakeholders to gather BRD/FRD, ensuring patient data accuracy, tracking interventions effectively, and maintaining full compliance with HIPAA and internal healthcare standards. Data Analyst Accenture, India Jun 2020 - Jul 2023

• Developed credit risk scoring and transaction anomaly detection models using regression analysis and probability distributions, accurately identifying high-risk clients, and enabling targeted interventions to reduce defaults and losses.

• Designed and implemented robust ETL pipelines integrating transactional, customer, and account datasets from PostgreSQL, ensuring validated and consistent datasets for predictive modeling and regulatory financial analytics.

• Built interactive Tableau and QlikView dashboards to visualize credit risk trends, unusual transaction patterns, and compliance alerts, empowering analysts, and managers with actionable insights for timely decision-making.

• Conducted comprehensive ad hoc data mining and exploratory analysis, identifying hidden patterns in account behavior, transaction anomalies, and demographic features to enhance predictive models and fraud prevention strategies.

• Applied advanced feature engineering and linear algebra techniques to transform raw financial data into predictive features, improving model accuracy and supporting data-driven decision-making for risk mitigation strategies.

• Orchestrated cloud-based data integration workflows in AWS, consolidating multi-source financial datasets securely and efficiently while maintaining compliance with regulatory standards and ensuring reliable analytics pipelines.

• Implemented DBT-based data modeling & version control through Git/GitHub, creating reproducible analytics pipelines, maintaining governance, & enabling seamless collaboration across finance analytics and data engineering teams.

• Developed SSRS reports and automated queries to monitor credit defaults, high-risk accounts, and fraud metrics, providing management with actionable insights for financial planning and risk mitigation.

• Performed hypothesis testing and statistical validation on predictive models, ensuring high confidence in risk and fraud predictions, supporting critical business decisions for credit approvals and fraud intervention.

• Collaborated with stakeholders following Waterfall methodology, gathering requirements, validating deliverables, & ensuring project milestones were achieved on schedule, aligning analytics solutions with organizational financial objectives.

• Leveraged advanced analytics and machine learning models, testing multiple algorithms to optimize fraud detection, credit risk predictions, and portfolio risk assessments, improving accuracy and reducing financial losses.

• Delivered insights through visualizations and executive summaries, enabling finance managers and leadership teams to make informed decisions that mitigated risk, prevented fraud, and enhanced profitability. EDUCATION

Master of Science in Data Science

– University of North Texas, Denton, Texas USA

Bachelor of Technology in Information Technology

– Jawaharlal Nehru Technological University Hyderabad, India CERTIFICATIONS

• Microsoft Azure Fundamentals: January 2023

• Data Center Visualization: January 2022

• Oracle AI Autonomous Database 2025 Certified Professional

• Oracle Cloud Infrastructure 2025 Generative AI Professional

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