Business Intelligence Data Analyst

Yoshitha Mudulodu

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

Mobile: +1-475-***-****

Data Analyst

PROFESSIONAL SUMMARY:

Over 5 years of experience leveraging analytical thinking and problem-solving skills to deliver actionable insights, demonstrating attention to detail across diverse projects and teams. Strong communication skills are used daily.

Expert in using SQL and PL/SQL to mine, transform, and analyze datasets, ensuring high-quality outputs that guide strategic decisions; adept at writing and analyzing complex queries. Team player.

Proficient in creating intuitive dashboards and KPIs, offering real-time visibility to stakeholders; ability to effectively communicate across the organization, both to technical and non-technical audiences.

Developed data ingestion pipelines to consolidate datasets, streamline reporting, and enable centralized access to critical business data, connecting dots across various applications for an E2E view.

Engineered robust ETL workflows to automate data cleansing and transformation using SQL, resulting in reduced processing times and improved data accuracy; works well in a team environment.

Conducted statistical modeling to identify behavioral patterns and support revenue-boosting initiatives; willingness to ask questions and reach out for assistance as required for team success.

Designed scalable data warehouses to optimize query performance and simplify data retrieval for analysis teams, demonstrating innovative thinking and attention to detail in data architecture.

Integrated cross-platform datasets using data lakes and cloud storage, building unified analytics ecosystems that facilitated faster reporting and richer business intelligence for executive leadership.

Implemented anomaly detection systems and alerting mechanisms to identify data inconsistencies, reduce operational risks, and improve data integrity across pipelines and data layers, with minimal supervision.

Delivered A/B testing solutions to support campaign analysis and content optimization, empowering teams to make evidence-based decisions using statistical confidence levels and analytical mindset.

Automated recurring data validation and reporting processes using Python scripts and scheduling tools, enabling faster delivery and reducing manual intervention in analytics tasks, identifying priorities.

Collaborated with stakeholders to gather evolving requirements and convert them into scalable, efficient data architectures and reporting frameworks tailored to unique operational needs, team player.

Documented all data flows, mapping rules, transformations, and dictionaries, ensuring data governance compliance and enabling seamless knowledge transfer across analytics and engineering teams.

Built machine learning models for classification, regression, and forecasting tasks, optimizing model performance through hyperparameter tuning and cross-validation techniques, managing multiple projects.

Experience with Oracle Exadata or 10g and above for large-scale data ingestion, processing, storage, and secure access control implementation, demonstrating strong PL/SQL skills and expertise.

Constructed end-to-end pipelines to support real-time analytics, improving data freshness and response time for business reporting dashboards, with proficiency in connecting dots across applications.

Implemented monitoring, setting up logging, alerting, and failure recovery protocols to ensure pipeline reliability, transparency, and adherence to SLAs, with attention to detail and problem-solving.

Applied IAM roles and VPC policies to enforce secure, role-based access to datasets and pipeline resources, ensuring compliance with internal data security protocols and team collaboration.

Used Git, Bitbucket, and CI/CD tools like Jenkins to maintain analytics codebases, streamline deployments, and enable version tracking and rollback capabilities for team development efforts.

Adept at explaining complex data topics to non-technical audiences, bridging the gap between data engineering and business strategy with clarity, accuracy, and actionable insights, effort estimation.

TECHNICAL SKILLS:

Languages - SQL, Python, R, PL/SQL

Visualization - Power BI, Tableau, Excel

Environments - Jupyter, RStudio, Google Colab, Oracle Exadata, Oracle 10g

Databases - SQL Server, PostgreSQL, MongoDB

Cloud Platforms - BigQuery, Dataflow, Google Cloud Storage, Azure Data Factory, Azure Synapse Analytics

Tools & Technologies - Git, CI/CD, ETL, Data Modeling, Machine Learning, APIs, Microsoft Office

Processes - Agile, Scrum

PROFESSIONAL EXPERIENCE:

LPL Financial July 2023 – Present

Data Analyst

Responsibilities:

Leveraged analytical thinking and problem-solving skills to design interactive Power BI dashboards, visualizing financial performance and improving transparency for leadership across finance and operations teams. This enhanced data-driven decision-making capabilities.

Conducted in-house Power BI training sessions for new analysts and business stakeholders, improving tool adoption and empowering users to explore self-service analytics and reporting. This improved team success.

Automated recurring weekly and monthly reporting pipelines using SQL and Python, reducing manual reporting efforts and eliminating processing errors across financial and client analytics. This improved attention to detail.

Partnered with data engineers, product managers, and business analysts to validate data definitions, improve schema consistency, and optimize reporting workflows for greater accuracy and usability. This improved communication.

Consolidated datasets from CRM, trading systems, and ERP sources to support regulatory compliance reporting, improving audit readiness and ensuring timely regulatory submissions. This required innovative thinking.

Built data monitoring solutions using Google Cloud tools to detect anomalies in transaction and portfolio data, enabling proactive issue resolution and improved system reliability. This improved analytical thinking.

Delivered tailored ad hoc visual reports to finance, sales, and portfolio strategy teams, translating technical outputs into actionable business insights and supporting critical decision-making processes. This improved communication.

Participated actively in agile ceremonies, including sprint planning, retrospectives, and daily stand-ups, ensuring alignment with team goals and maintaining transparency across development cycles. This improved team success.

Developed and deployed a dynamic forecasting model using historical financial trends, increasing budget planning accuracy by 25% and aligning projections with real-world market conditions. This improved problem solving.

Created and optimized SQL stored procedures to automate data cleansing and transformations on financial transaction data, ensuring consistency and integrity across downstream analytics systems. This improved attention to detail.

Elevance Health May 2022 – June 2023

Data Analyst

Responsibilities:

Developed healthcare analytics reports on member claims, utilization metrics, and provider network behaviors to support business planning, care optimization, and regulatory reporting efforts. This improved analytical thinking.

Created interactive Tableau dashboards tracking value-based care program outcomes and health intervention performance, enabling executive-level insights and proactive performance management. This improved communication.

Applied regression, survival analysis, and cohort evaluation methods to assess the effectiveness and impact of clinical treatment plans across Medicaid and Medicare populations. This improved problem solving.

Combined clinical, demographic, and administrative data sources to deliver holistic insights on population health, disease prevalence, and social determinants of health trends. This improved attention to detail.

Led cost analysis initiatives to identify areas for financial optimization, uncovering over $1 million in potential savings across member claims and provider contract structures. This improved innovative thinking.

Tuned and restructured complex SQL queries used in recurring reports, resulting in a 30% reduction in execution time and improved dashboard refresh rates. This improved attention to detail.

Responded to high-priority ad hoc requests from healthcare operations and finance teams, delivering custom datasets and visual reports tailored to urgent stakeholder needs. This improved communication.

Conducted routine audits of inbound data feeds to identify quality issues, inconsistencies, and transformation failures, followed by comprehensive root cause analysis reports. This improved analytical thinking.

Built and maintained ETL pipelines using SQL and Python to ingest payer and provider data, enabling integration of operational and clinical datasets into analytics platforms. This improved problem solving.

Created and distributed regulatory submission reports supporting Medicaid and Medicare compliance programs, ensuring timeliness and alignment with CMS specifications. This improved attention to detail.

Cognizant Pvt. Ltd November 2019 – July 2021

Junior Data Analyst

Responsibilities:

Supported business intelligence operations for finance and logistics clients by preparing detailed reports, ensuring data consistency, and assisting in the execution of insights-driven project deliverables. This improved analytical thinking.

Created robust ETL workflows using SQL to ingest, standardize, and load customer and operations data from varied formats into internal databases for analysis and reporting. This improved attention to detail.

Developed Excel-based KPI dashboards to track performance metrics, service-level compliance, and exception trends across operational, procurement, and financial departments. This improved communication.

Maintained and enhanced legacy reporting systems by upgrading tools and migrating reports to modern platforms like Tableau and Power BI for improved performance and usability. This improved problem solving.

Collaborated with senior analysts on data visualization design, narrative construction, and dashboard assembly for external client presentations and internal strategic reviews. This improved team success.

Executed QA testing on newly developed data pipelines and BI reports, validating logic, field mappings, and transformation accuracy across test and production environments. This improved attention to detail.

Authored detailed documentation outlining ETL process logic, transformation mappings, and job scheduling dependencies for internal use and project handover purposes. This improved communication.

Participated in data migration projects from on-premises SQL servers to cloud platforms, contributing to improved scalability, accessibility, and system resilience. This improved problem solving.

Led reconciliation efforts to identify discrepancies between legacy and cloud-based data stores, using automated queries and manual reviews to ensure data parity post-migration. This improved analytical thinking.

Created complex Excel macros to automate data formatting, aggregation, and cleanup processes, reducing manual effort and improving accuracy in daily reporting activities. This improved attention to detail.

Certifications:

Google Data Analytics Professional Certification – Google

Excel for Business – Coursera

AI-Driven Analytics Simulation – Tata Consultancy Services

Educational Details:

Master of Science in Computer Science - University of Bridgeport, CT

Bachelor of Technology in Computer Science - Keshav Memorial Institute of Technology, India

Contact this candidate