Anmisha Mandalapu
Data Analyst • United States • a******************@gmail.com • +14******288 • linkedin.com/••••• • drivetube.ai/•••••
Professional Summary
Data Analyst with 2+ years of experience specializing in SQL, Python, Power BI, Tableau, ETL automation, and statistical analysis to transform complex data into actionable business insights. Proven track record building automated ETL pipelines, optimizing SQL performance, and delivering interactive dashboards that reduced manual reporting time by up to 60% and improved reporting accuracy by 28%. Skilled at partnering with cross-functional teams to translate business requirements into KPI-driven analytics and operational improvements.
Technical Skills
Programming Languages: Python
Frameworks and Libraries: Pandas,NumPy,SciPy,Matplotlib
Databases: PostgreSQL,MySQL,Microsoft SQL Server,Supabase
Data and Analytics: Power BI,Tableau,Microsoft Excel,Hypothesis Testing,Chi-Square Test,T-Test,Descriptive Statistics,Data Segmentation,ETL Automation,Data Pipelines,Workflow Automation,Data Cleaning,Data Validation
Tools and Methodologies: GitHub
Automation & APIs: n8n,Tavily API
Work Experience
Verizon
United States
Data Analyst
Jun 2025 – Present
Telecommunications leader Verizon; analysis of customer usage, billing and network performance data supported marketing, finance and customer-operations decisions company-wide.
Tech Stack: Python, SQL, PostgreSQL, Microsoft SQL Server, Power BI, n8n, Supabase, Pandas, NumPy, SciPy, GitHub, Microsoft Excel
- Analyzed customer usage, billing, and network performance datasets using SQL and Python on PostgreSQL to detect behavior patterns; insights informed retention strategies and improved campaign effectiveness by 18%.
- Built interactive Power BI dashboards tracking churn, revenue, and network KPIs; consolidated multiple manual reports into a single self-service portal, cutting manual reporting effort by 45%.
- Optimized complex SQL queries and stored procedures on Microsoft SQL Server and PostgreSQL, refactoring joins and indexes to reduce report runtime and improve reporting performance by 35%.
- Automated ETL workflows and data validation using Python, n8n, Supabase, and SQL to standardize ingest and reconciliation; reduced manual data preparation time by 60% while increasing dataset reliability.
- Partnered with Marketing, Finance, and Customer Operations to translate business needs into measurable KPIs and reports; delivered actionable insights that supported decision-making across four business units.
- Applied statistical tests (hypothesis testing, Chi-Square, T-Tests) to validate A/B experiments and customer engagement initiatives, increasing stakeholder confidence in recommendations by 30%.
CVS Health
United States
Data Analyst
Jan 2024 – May 2025
Healthcare and pharmacy enterprise CVS Health; analytics on pharmacy operations, claims, and transactions drove KPI dashboards for prescription, inventory and operational performance.
Tech Stack: Python, SQL, Microsoft SQL Server, Power BI, Tableau, n8n, Supabase, Pandas, NumPy, Microsoft Excel, GitHub
- Analyzed pharmacy operations, claims, and transaction data with SQL and Python on Microsoft SQL Server to identify reporting gaps; changes improved reporting accuracy by 28%.
- Designed and delivered Power BI and Tableau dashboards presenting prescription volumes, inventory KPIs, and operational metrics, reducing report preparation time by 40%.
- Implemented automated data cleaning, validation, and reconciliation scripts in Python and SQL to resolve data quality issues across claims and pharmacy systems, increasing data consistency by 32%.
- Built end-to-end ETL pipelines and scheduled reporting workflows using Python, SQL, n8n, and Supabase to ensure timely, accurate data delivery; reduced manual reporting effort by 50%.
- Collaborated with pharmacy operations, finance, and business stakeholders to gather requirements and prioritize analytics, enabling data-driven decisions across multiple business units.
- Documented reporting logic and validation rules and maintained dashboard user guides, streamlining handoffs and reducing stakeholder clarification requests during monthly close cycles.
Healthcare
Education
Lamar University
Master of Science in Computer Science • Texas • Aug 2022 – Apr 2024
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