Data Analyst Continuous Improvement

SANTHOSHVISHWANADULA

Email: *********************@*****.***

Mobile: +1-786-***-****

Data Analyst

PROFESSIONAL SUMMARY:

• Data Analyst with 5+ years of experience analyzing logistics invoice data, ensuring accuracy and compliance, supporting timely revenue collections, and optimizing services for clients, demonstrating strong analytical skills.

• Designed and implemented advanced data analysis and data analytics solutions using Excel and Power BI to develop dashboards that support business needs, monitor trends, and improve operational performance.

• Proficient in SQL queries to gather data, perform data wrangling, cleaning, and transformation, improving data consistency and enabling accurate analysis and reporting outputs for continuous improvement projects.

• Built efficient ETL pipelines to centralize operational reporting, reducing manual data handling and errors; located and defined continuous improvement opportunities leveraging digital automation tools to increase task efficiency.

• Conducted statistical analysis using regression and hypothesis testing to identify trends, patterns, and relationships in complex datasets within the logistics and finance sectors to support data-driven strategies.

• Automated daily and weekly reporting tasks using scripting and SQL queries, significantly reducing reporting cycles and freeing time for more strategic, exploratory data tasks while ensuring accuracy and attention to detail.

• Developed solutions utilizing data analysis and advanced analytics to support business needs, improve retention metrics across target segments, and enhance client satisfaction through effective communication.

• Automated weekly and ad-hoc reports using Python scripting and SQL queries to reduce time spent on recurring tasks, freeing analysts’ time by 80% for more strategic, exploratory data tasks.

• Collaborated with stakeholders to define business and information needs, design data collection strategies, and deliver executive-ready dashboards with self-service capabilities for effective decision-making.

• Cleaned and merged datasets from APIs, databases, and Excel sources into analysis-ready formats, ensuring data quality, accuracy, and seamless integration with downstream reporting workflows, improving financial practices.

• Analyzed and redesigned legacy data warehouse schemas, applying best practices in dimensional modeling and indexing, which significantly improved data retrieval speeds and report performance for internal teams.

• Built data-driven reports using SQL with window functions, case logic, and subqueries that empowered stakeholders to make operational decisions, identifying optimization and cost-saving opportunities for the business.

• Integrated and normalized third-party APIs and internal systems to establish unified business intelligence environments, enabling consistent enterprise reporting and real-time decision-making with connected analytics platforms.

• Worked closely with data engineering teams to define schema standards, ingestion schedules, and transformation rules for Azure Data Factory and Synapse workflows, ensuring enterprise-level data reliability and lineage.

• Queried large-scale datasets in Azure Synapse using optimized T-SQL and built robust views to serve as sources for downstream Power BI reports, significantly accelerating business intelligence turnaround times.

• Analyzed marketing campaign performance using data extracted from Google Analytics and CRM tools, calculating ROI, CAC, and retention metrics to recommend changes that led to a 23% improvement in ROI.

• Designed and interpreted A/B tests using statistical analysis in Python and Excel, offering insight into user behavior, conversion rates, and marketing strategies that directly influenced product and campaign strategies.

• Implemented data quality checks, encryption standards, and access controls in alignment with HIPAA and company security policies, maintaining full compliance while supporting analytics and business operations needs.

• Maintained detailed data dictionaries, transformation documentation, and lineage diagrams in Confluence, providing transparency, traceability, and faster onboarding for new analysts joining enterprise-level projects.

• Engaged with clients via email and calls, including discussion on past due balances and working towards getting resolution on open balances, demonstrating excellent communication skills and self-motivation. TECHNICAL SKILLS:

• Languages - Python, SQL, R

• Databases - MySQL, SQL Server, PostgreSQL

• Visualization Tools - Power BI, Tableau

• Tools & Platforms - Azure Synapse, Azure Data Factory, GCP, AWS, Google Analytics, SharePoint, OneDrive, Digital Automation Tools, RPA

• Libraries - Pandas, NumPy, Scikit-learn, Statsmodels, Matplotlib, Seaborn

• Other - Git, Jupyter, Excel (Advanced), REST APIs, Reporting Tools PROFESSIONAL EXPERIENCE:

UnitedHealth Group December 2024 – Present

Data Analyst

Responsibilities:

• Gathered and analyzed logistics invoice data using SQL queries to research order charges, ensuring accuracy and compliance with financial practices, directly supporting revenue collections and optimization efforts. This involved identifying trends and patterns in complex datasets to improve financial reporting.

• Developed and implemented advanced data analysis and data analytics solutions using Power BI to support business needs, providing actionable insights to senior leadership for strategic decision-making and continuous improvement opportunities. This streamlined invoice processing.

• Identified trends, patterns, and relationships in complex datasets within the healthcare and finance sectors, providing critical insights for continuous improvement initiatives, operational efficiency gains, and accurate financial forecasting. These insights supported timely revenue collections.

• Utilized Excel and Power BI to develop and implement data analytics solutions, creating dashboards and analytical/reporting tools that provide real-time updates on key performance indicators, contributing to efficient financial practices and reporting accuracy.

• Engaged with internal clients via email and calls to discuss past due balances and work towards resolution, ensuring timely revenue collections and optimizing financial practices within the healthcare ecosystem. This improved invoice data quality.

• Prioritized business and information needs in collaboration with senior leadership, aligning data analysis efforts with strategic objectives to drive continuous improvement and optimize revenue collection processes across healthcare operations. This ensured accurate invoicing.

• Located and defined continuous improvement opportunities and leveraged digital automation tools to increase efficiency of tasks related to data analysis and reporting, enhancing financial practices and contributing to revenue optimization strategies.

• Demonstrated strong analytical skills by collecting, organizing, analyzing, and disseminating significant amounts of logistics invoice data with attention to detail and accuracy, supporting accurate invoicing and financial compliance, resulting in revenue collections.

• Applied strong communication skills for internal collaboration and presentations to stakeholders on data- driven insights, ensuring a clear understanding of data analysis findings and their impact on financial practices and reporting accuracy for executives.

• Managed multiple projects effectively, demonstrating high self-motivation and organization, to support accurate invoicing, timely revenue collections, and optimized financial practices across diverse healthcare operations with various logistics needs.

NTT DATA Services May 2019 – May 2023

Junior Data Analyst

Responsibilities:

• Gathered data using reporting tools and SQL queries to analyze logistics invoice data, ensuring accuracy and compliance with financial practices for internal clients across multiple departments, which supported accurate invoicing workflows and transparency.

• Utilized Excel and Power BI to develop & implement data analytics solutions, providing updates via dashboards and other analytical/reporting tools, enhancing financial practices and improving reporting turnaround time for various operational teams.

• Identified trends, patterns, and relationships in complex datasets within the logistics and finance sectors, contributing to process improvement initiatives and reporting cycles while working with cross-functional teams, which provided valuable business insights.

• Supported the implementation of advanced data analysis and data analytics solutions to meet business needs, working closely with senior analysts on complex reporting projects and dashboard development related to invoice data workflows.

• Engaged in ongoing research projects, collecting and analyzing feedback using SharePoint and OneDrive files, to contribute to the continuous improvement of data analysis methodologies and financial practices in support of invoice data.

• Developed and implemented advanced data analysis techniques, which helped improve the quality and consistency of metrics shared with cross-functional teams for process improvement initiatives and reporting cycles related to invoice data.

• Located and defined continuous improvement opportunities by leveraging digital automation tools to increase the efficiency of tasks, such as data extraction, transformation, and loading, to improve overall invoice workflow management and transparency.

• Applied strong communication skills for internal collaboration and presentations to stakeholders on data- driven insights related to invoice data, ensuring a clear understanding of data analysis findings and their impact on reporting accuracy, enabling better business decisions.

• Demonstrated strong analytical skills by collecting, organizing, analyzing, and disseminating significant amounts of logistics invoice data with attention to detail and accuracy, ensuring compliance with financial practices, enhancing invoice accuracy.

• Applied knowledge of financial concepts and experience in the logistics industry by analyzing logistics invoice data, which helped optimize services for clients and identify opportunities to enhance financial practices, contributing to timely revenue collections. Certifications:

• Data Analysis with Python – IBM

• Python for Data Science – IBM

• MySQL Command Line – IBM

• AWS Certified Cloud Practitioner

• CodePath Advanced Technical Interview Prep

Educational Details:

Master of Science in Data Science & Analytics - Florida Atlantic University Bachelor of Technology in Computer Science - Jawaharlal Nehru Technological University Hyderabad

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