Data Analyst SQL - Python - BI Dashboards

Pavithra Surapaneni

Atlanta, GA (Open to relocate) +1-943-***-**** *******************@*****.*** SUMMARY

Data Analyst with 3 years of experience delivering SQL-driven analytics, Python-based data processing, and BI dashboards for business and operational decision-making. Strong expertise in data cleaning, exploratory data analysis, KPI development, data modeling, and stakeholder reporting, with hands-on exposure to cloud data platforms, ETL pipelines, and Agile delivery.

EDUCATION

Master of Science, Business Analytics

Mercer University, USA Aug 2023 - May 2025

Bachelor of Pharmacy

BITS Pilani Hyderabad Campus, India Aug 2018 - Jun 2022 SKILLS

● Data Analysis and Statistics: Exploratory Data Analysis, Statistical Analysis, Trend Analysis, Forecasting, Time Series Analysis, A/B Testing

● Programming and Querying: SQL, Python

● Visualization: Power BI, Tableau, Looker, Data Visualization, KPI Dashboards, Executive Reporting

● Data Engineering and Cloud: ETL Pipelines, Data Modeling, Data Warehousing, Snowflake, BigQuery, AWS

● Business and Requirements Analysis: Requirement Gathering, Stakeholder Management, BRD, FRD, User Stories, Acceptance Criteria

● Data Quality and Governance: Data Validation, Data Reconciliation, Data Quality Checks, Documentation

● Tools and Methodologies: Advanced Excel, JIRA, Confluence, Agile Scrum PROFESSIONAL EXPERIENCE

Humana, Location

Data Analyst Jan 2025 - Current

● Analyzed 1.2M+ transactional and customer records using advanced SQL (joins, CTEs, window functions) and exploratory data analysis to identify revenue, churn, and conversion trends, influencing decisions that improved ROI by 18%.

● Automated recurring business and operational KPI reporting using Power BI, DAX, SQL views, and Power Query, reducing manual Excel-based reporting effort by 35% and supporting 6 business stakeholders.

● Performed data cleaning, transformation, and validation using Python (Pandas, NumPy), handling missing values, duplicates, and outliers, improving dataset accuracy and reliability by 28%.

● Built and optimized dimensional data models (star schema) and tuned SQL query performance through indexing and refactoring, reducing dashboard refresh time from 18 min to 14 min (22%).

● Conducted exploratory data analysis, statistical summaries, and trend analysis to support ad-hoc leadership requests, reducing insight turnaround time by 16%.

● Collaborated with 3 data analysts and 2 QA/data validation analysts to reconcile source systems, perform data quality checks, and validate KPI calculations, reducing reporting discrepancies by 24%. Syneos Health, Location

Data Analyst Jan 2021 - Jul 2023

● Led requirement gathering sessions with 4 cross-functional stakeholders across Sales, Operations, and Finance, documenting BRDs, user stories, and acceptance criteria aligned to reporting and analytics needs.

● Defined, standardized, and documented KPIs and business metrics, improving metric alignment across teams and reducing data-related clarification cycles by 27%.

● Developed SQL datasets and Excel-based analytical models using Power Query, pivot tables, and formulas to support pricing analysis, demand forecasting, and operational planning, improving forecast accuracy by 17%.

● Designed interactive Tableau dashboards with filters, drill-downs, and trend analysis for executive and operational reviews, reducing ad-hoc data requests by 31%.

● Supported UAT, reconciliation, and data validation activities with 1 QA analyst, validating source-to-target mappings and calculations, reducing post-release reporting defects by 23%.

● Managed analytics-related JIRA tickets and supported Agile sprint execution by clarifying requirements, prioritizing backlog items, and coordinating data readiness, improving on-time reporting delivery by 15%. PROJECTS

Business Performance Analysis Dashboard

● Analyzed 300K+ business and operational records using SQL, Python, and Excel to evaluate performance trends and reporting accuracy.

● Cleaned, validated, and reconciled datasets, improving data quality and consistency by 25% across source files.

● Conducted exploratory data analysis and KPI analysis to identify growth and efficiency gaps, reducing insight turnaround time by 20%.

● Built interactive Power BI dashboards with KPI tracking and trend analysis, reducing manual reporting effort by 30%.

● Delivered data-driven insights and documentation to stakeholders, improving decision-making efficiency by 15%.

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