Data Analyst Business Intelligence

Shivaramakrishna Reddy Kasireddy

Data Analyst

Washington, USA 551-***-**** *************@*****.*** LinkedIn Summary

• Results-driven Data Analyst with 5+ years of experience in healthcare and finance, skilled in SQL, Python, and Excel to conduct data mining, statistical analysis, and business intelligence reporting for enterprise systems.

• Assembled automated data pipelines using Azure Data Factory, Apache Airflow, and Informatica, reducing ETL run time by 45% while enhancing data governance, audit tracking, and real-time financial and clinical data processing.

• Applied advanced analytics, machine learning, and predictive modeling in Python (pandas, NumPy, scikit-learn) to identify patient risk factors and financial fraud patterns, improving data-driven decisions and operational efficiency.

• Developed executive dashboards using Power BI, Tableau, and Looker to track clinical KPIs, revenue cycle metrics, and regulatory compliance, enabling leadership to act on actionable insights with real-time visual analytics.

• Partnered with stakeholders, data engineers, and product teams to define requirements, optimize relational databases, and implement dimensional data models, improving data lineage, scalability, and data warehouse performance.

• Proficient with cloud platforms (AWS, Azure) and ERP & CRM systems (SAP, MS Dynamics Nav, Salesforce, HubSpot)

• Performed data wrangling, normalization, and validation using SQL, Alteryx, and R, ensuring HIPAA, SOX, and GDPR compliance while improving data accuracy for financial reporting and patient outcomes tracking by 30%. Technical Skills

Programming Languages: Python (pandas, NumPy, Matplotlib, Seaborn), R, SAS Databases & Query Languages: SQL, NoSQL (MongoDB)

Data Processing & ETL Tools: Apache Airflow, Talend, Informatica, SSIS Data Warehousing: Amazon Redshift, Snowflake, Google BigQuery Cloud Platforms: AWS, Azure

Data Visualization & Reporting: Power BI, Tableau, Excel (Advanced, VBA), SSRS ML & Data Science: Scikit-learn, TensorFlow, Predictive Modeling, Data Mining, Clustering, Classification, Regression, A/B Testing, Forecasting

Data Management & Quality: Data Wrangling, Data Cleaning, Talend Data Quality, Alation, Data Governance, Encryption, Masking, GDPR, HIPAA

HealthCare Tools & Standards: Cerner, HL7, ICD-10, CPT Version Control & Collaboration: Git, GitHub, JIRA, Confluence Other Skills: Ad Hoc Analysis, EHR, Process Mapping, Requirement Gathering, Root Cause Analysis, Data Storytelling, Data Presentation, Solution Design, Project Management

(551) 309-2666Professional Experience

Data Analyst Optum WA, USA Jan 2024 - Present

• Spearheaded advanced care pathway analytics using SQL, Python, AWS Athena, Excel, dbt, and Power BI to enhance patient journey visibility, optimize transitions of care, and reduce avoidable utilization across two major hospital systems.

• Conducted advanced cohort analysis and member segmentation using Python (Pandas, NumPy) to identify cost and utilization patterns across chronic condition populations such as diabetes and heart failure, revealing 15% of the population accounted for 24% of total healthcare costs.

• Integrating Electronic Health Record (EHR) data into analytical workflows, ensuring a comprehensive view of patient health.

• Built a readmission prediction pipeline using Python, applying logistic regression on EMR and claims datasets to forecast cardiology patient risk levels, enabling proactive outreach and reducing 30-day readmission rates by 17% hospital-wide.

• Engineered denial root cause dashboards in Power BI, integrating multi-source claims, pre-authorization, and scheduling data to visualize real-time approval bottlenecks; enhanced administrative transparency and enabled operational leaders to implement targeted interventions, reducing claim denials by 23% across service lines.

• Scripted dynamic provider scorecards in Excel, calculating referral volumes, productivity KPIs, and compliance thresholds; enabled data-driven specialty realignment and workforce planning, significantly increasing value-based reimbursement eligibility across three low-performing regions and improving overall provider network efficiency.

• Designed multimorbidity stratification models using AWS Athena, extracting ICD-10 data from EMRs to identify elderly high-risk populations, enhancing care coordination strategies and improving chronic disease program targeting accuracy.

• Modeled surgical block scheduling using dbt, simulating OR throughput constraints and enabling procedural rescheduling; resulting efficiency improvements led to a 28% increase in first case on-time starts across three hospital campuses.

• Integrated HIPAA-compliant CMS audit workflows using Apache Airflow, replacing error-prone manual tracking with robust DAG-based pipelines, improving audit trail traceability and reducing weekly regulatory submission cycle time by 65%.

• Refactored outdated clinical ETL pipelines with SQL, restructuring transformation logic to reduce execution failures by 70%, decrease data latency, and increase SLA adherence for time-sensitive clinical performance dashboards.

• Linked multi-source coordination data using Airflow, integrating Jira, EMR, and CRM inputs to trace care handoff metrics, reducing referral delays and increasing specialty follow-up adherence by 20% system wide.

• Facilitated pharmacy spend anomaly detection using AWS S3, aggregating cost patterns across prior authorization data to uncover drug formulary deviations, saving $650K in six months through workflow adjustments.

• Collaborated on predictive analytics deployment using TensorFlow, refining deep learning models for patient safety insights and supporting high-stakes decisions in hospital-wide initiatives for quality, safety, and financial sustainability. Data Analyst Deloitte India Jun 2019 – Aug 2022

• Executed end-to-end banking analytics initiatives using SQL, Excel VBA, Python, Scikit-learn, Seaborn, Tableau, Talend, Informatica, PostgreSQL, and AWS S3, enabling campaign optimization, payment automation, underwriting refinement, and compliance reporting across financial systems, driving efficiency and strategic alignment.

• Constructed credit utilization prediction models using Python, analyzing transaction-level behavioral trends to enable dynamic customer segmentation; insights were integrated into CRM workflows, improving targeting precision, enhancing portfolio growth strategy, and increasing high-value account acquisition rates by 21% across four fiscal quarters.

• Illustrated executive performance dashboards in Tableau, visualizing real-time loan processing SLAs, approval turnaround times, and risk exposure thresholds to support strategic decision-making, reduce processing delays, and surface borrower eligibility bottlenecks across high-volume consumer and commercial lending portfolios.

• Refined disbursement reconciliation workflows using SQL, streamlining multi-source financial data integration, resolving data duplication issues, and aligning outputs with audit controls; improvements reduced backlog by 42%, improved data accuracy, and strengthened quarterly financial compliance for internal and external audits.

• Conducted market volatility analysis using Seaborn, profiling asset-level price fluctuations across equities, bonds, and derivatives; insights informed portfolio strategy adjustments during two major fiscal shocks, minimizing downside exposure.

• Produced modular data ingestion templates using Talend, standardizing POS transaction feeds and improving ingestion throughput by 34%, enabling near-real-time financial reporting across enterprise business intelligence platforms.

• Orchestrated exception handling workflows in KYC systems using SSIS, configuring advanced data flow tasks to detect incomplete onboarding documentation; optimized compliance pipelines reduced SLA violations by 38% and strengthened regulatory adherence across enterprise-wide customer identity verification and audit tracking systems.

• Created time-series anomaly detection models with Scikit-learn, analyzing SME transaction flows to flag suspicious patterns; risk alerts enabled pre-emptive fraud reviews, enhancing regulatory response across high-risk financial products.

• Streamlined marketing campaign analytics using Excel VBA, enabling dynamic KPI tracking dashboards that supported real-time optimization decisions and boosted conversion rates across three digital channels by 26% over six months.

• Implemented unified reporting layers using Informatica, integrating financial data across vendor, customer, and invoice systems; increased end-to-end auditability and data traceability for internal risk and external regulatory teams.

• Contributed with pricing analysts and compliance teams using Azure Data Factory to orchestrate ingestion pipelines for behavioral variables, reduced data latency and improved resource planning in global pricing strategies. Education

University of Maryland, Baltimore County, Maryland, USA Master of Science in Data Science

Jawaharlal Nehru Technological University, Telangana, India Bachelor of Technology in Computer Science

Certifications

• Microsoft Fabric Analytics Engineer Associate

• Google Data Analytics Professional Certificate

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