Data Analyst Business Intelligence

Ruthiksha Reddy Yenugu

Contact: +1-940-***-**** Email: ********************@*****.*** LinkedIn

Data Analyst with Expertise in Advanced Analytics & Business Intelligent Systems

Data Analyst with 4+ years of specialized expertise in transforming complex multi-source datasets into strategic business intelligence solutions across healthcare, financial services, and insurance sectors. Distinguished track record in developing high-performance analytical frameworks, optimizing data processing workflows, and delivering real-time business insights that drive measurable operational improvements. Expert in statistical analysis, advanced visualization, and cloud-based data architecture with proven ability to translate technical findings into executive-level strategic recommendations.

Advanced Statistical Analysis Business Intelligence Development Data Pipeline Architecture Performance Analytics Fraud Analytics Systems Healthcare Data Analysis Cloud Data Platforms Executive Reporting Query Optimization Cross-Functional Analytics Stakeholder Engagement Process Automation Data Governance

PROFILE SYNOPSIS

Expert in developing sophisticated analytical frameworks using advanced SQL techniques, Python scripting, and statistical methodologies to extract actionable insights from high-volume datasets exceeding 50GB daily processing capacity.

Proven expertise in architecting enterprise-grade data pipelines utilizing modern ETL tools (Airflow, dbt, Spark) and cloud platforms to ensure 99.9% data accuracy and sub-second query response times for critical business reporting.

Advanced proficiency in statistical analysis and hypothesis testing employing regression modeling, time-series forecasting, and correlation analysis to identify trends, patterns, and anomalies that drive strategic business decisions.

Demonstrated success in building executive-level business intelligence solutions using Tableau, Power BI, and custom Python visualizations that translate complex analytics into actionable business recommendations for C-level stakeholders.

Exceptional ability in cross-functional collaboration with business analysts, IT teams, compliance officers, and executive leadership to align analytical initiatives with organizational objectives and regulatory requirements.

Specialized in performance optimization and cost reduction through advanced query tuning, automated reporting systems, and cloud resource optimization strategies that maximize analytical ROI and operational efficiency.

Expert in data governance and quality assurance implementing comprehensive validation frameworks, audit trails, and regulatory compliance protocols ensuring data integrity across all analytical processes.

COMPETENCY MATRIX

Core Analytics Skills

Technical Proficiencies

Statistical Analysis & Modeling

Descriptive Statistics, Inferential Statistics, Hypothesis Testing, Regression Analysis, Time Series Analysis, Correlation Analysis, A/B Testing, Statistical Significance Testing, Scikit-learn, XGBoost, LightGBM, CatBoost

Programming & Development

Python (Pandas, NumPy, Scikit-learn), Advanced SQL (Window Functions, CTEs, Stored Procedures), R Programming, PL/SQL, T-SQL, FastAPI, Flask

Data Visualization & BI

Tableau (Advanced Calculations, Parameters), Power BI (DAX, Power Query, Custom Visuals), Excel (VBA, Advanced Functions), Matplotlib, Seaborn, Interactive Dashboards, Executive Reporting

Data Engineering & ETL

Apache Airflow, dbt, Apache NiFi, ETL Pipeline Development, Data Transformation, Real-time Processing, Batch Processing, Data Integration, Data Validation

Database & Big Data Technologies

PostgreSQL, MySQL, MongoDB, SQLite, SQL Server, Redshift, BigQuery, Snowflake, Apache Spark, Hadoop, Apache Hive, Elasticsearch, Query Optimization

Cloud Data Platforms

AWS (SageMaker, S3, Redshift, RDS, Lambda), Azure (AKS, Data Factory, Synapse), GCP (BigQuery, Cloud Storage, Dataflow), Cloud Migration, Serverless Analytics

Advanced Analytics & AI

Machine Learning Algorithms, Deep Learning (TensorFlow, PyTorch, Keras), Natural Language Processing (spaCy, NLTK, Hugging Face Transformers), Predictive Modeling

Development & DevOps Tools

Git Version Control, Docker, Kubernetes, MLflow, Apache Kafka, TSFresh, Featuretools, Jupyter Notebooks, Agile Methodologies, CI/CD Pipelines

Industry-Specific Analytics

Financial Risk Analytics, Healthcare Outcomes Analysis, Insurance Claims Analytics, Fraud Detection Systems, Regulatory Compliance Reporting, Real-time Anomaly Detection

PROFESSIONAL EXPERIENCE

Data Analyst Huntington National Bank May 2024 – May 2025

Key Achievements:

Developed comprehensive fraud analytics system processing 2M+ daily banking transactions through advanced statistical analysis and anomaly detection techniques, achieving 60% reduction in fraud losses equivalent to $15M+ annual savings through real-time pattern recognition.

Architected data processing infrastructure using Apache Airflow and AWS Redshift, reducing analytical query execution time by 85% and enabling real-time fraud monitoring across 500+ banking locations with sub-second alert capabilities.

Implemented statistical modeling framework utilizing time-series analysis, correlation studies, and behavioral pattern recognition, improving fraud detection accuracy from 72% to 94% precision while reducing false positive alerts by 45%.

Designed automated reporting and monitoring systems using Python automation scripts and cloud scheduling, processing 50GB+ daily transaction data with 99.9% uptime and comprehensive error handling protocols.

Created executive-level analytics dashboard suite featuring 15+ interactive Power BI reports with DAX calculations, predictive trend analysis, and risk heat maps driving adoption across fraud, compliance, and risk management departments.

Led data-driven business optimization initiatives coordinating with 12+ cross-functional stakeholders to implement integrated analytical solutions supporting strategic decision-making processes.

Key Deliverables:

Engineered production-grade ETL pipelines handling structured and unstructured banking data with automated data quality checks and exception handling mechanisms ensuring 99.8% processing accuracy.

Developed advanced SQL optimization strategies including query refactoring, index optimization, and execution plan analysis, reducing database resource consumption by 40% across critical reporting systems.

Implemented comprehensive data validation frameworks using Python and statistical testing methods, establishing automated anomaly detection for incoming data streams and maintaining data integrity standards.

Created detailed analytical documentation and conducted technical training sessions for junior analysts on advanced SQL techniques, statistical analysis methods, and business intelligence best practices.

Collaborated with cybersecurity and compliance teams to ensure regulatory adherence (PCI-DSS, banking regulations) across all data processing workflows and analytical outputs.

Established KPI monitoring systems tracking analytical performance metrics, system reliability, and business impact measurement for continuous improvement initiatives.

Data Analyst Apollo Hospitals, Hyderabad Oct 2022 – Jul 2023

Key Achievements:

Developed predictive analytics framework analyzing 100K+ patient EMR records using advanced statistical modeling and regression analysis, contributing to 35% reduction in hospital readmission rates and $2M+ annual cost savings through early intervention strategies.

Engineered automated clinical analytics system integrating real-time patient monitoring data with historical trends analysis, enabling data-driven clinical decision support and improving patient outcome predictions by 28% accuracy.

Built comprehensive healthcare business intelligence platform using Python, PostgreSQL, and Tableau, processing multi-structured medical data including lab results, diagnostic reports, and clinical documentation for population health insights.

Implemented advanced data processing workflows for medical time-series analysis, incorporating statistical significance testing and clinical indicator correlation studies to enhance analytical accuracy and clinical applicability.

Created real-time operational analytics dashboards monitoring 25+ critical hospital KPIs including bed occupancy rates, patient flow optimization, and resource utilization with automated alerting and trend analysis capabilities.

Established automated reporting infrastructure using Apache Airflow scheduling and Python scripting, reducing manual reporting effort by 80% and ensuring consistent delivery of analytical insights to clinical and administrative leadership.

Key Deliverables:

Designed comprehensive ETL workflows integrating disparate healthcare data sources including EMR systems, laboratory databases, and imaging archives with 99.5% data integrity and HIPAA compliance maintenance.

Developed statistical analysis protocols for clinical research studies including survival analysis, cohort studies, and treatment effectiveness evaluation using advanced Python libraries and R statistical packages.

Implemented data quality assurance frameworks for healthcare analytics ensuring clinical data standards adherence and automated validation across all analytical processes and reporting systems.

Created analytical documentation and clinical reporting templates enabling standardized insights delivery to physicians, nurses, and hospital administrators for evidence-based decision making.

Collaborated with medical professionals to translate clinical requirements into technical analytical specifications and develop domain-specific business intelligence solutions.

Associate Data Analyst Aditya Birla Sun Life Insurance Aug 2020 – Sep 2022

Key Achievements:

Architected automated claims processing analytics system using Python scripting and SQL stored procedures, achieving 70% reduction in processing time while maintaining 98% accuracy rate across 10K+ monthly claims validation workflows.

Developed comprehensive fraud detection analytics combining statistical rule-based analysis with pattern recognition algorithms, identifying suspicious claim patterns and reducing fraudulent payouts by $1.2M annually through data-driven investigation protocols.

Engineered enterprise-scale ETL infrastructure using Informatica and Apache NiFi, integrating 15+ disparate insurance data sources while maintaining 99.7% data quality across claims processing and regulatory reporting workflows.

Implemented predictive analytics for claims forecasting utilizing time-series statistical analysis and seasonal trend decomposition, optimizing resource allocation during peak claim periods with 92% forecasting accuracy.

Built comprehensive Tableau analytics ecosystem featuring 20+ interactive dashboards for claims monitoring, risk assessment analytics, and operational efficiency tracking across regional insurance offices.

Led process automation and optimization initiatives resulting in 85% reduction in manual data processing, improved data consistency standards, and enhanced regulatory compliance reporting capabilities.

Key Deliverables:

Designed robust data validation and quality assurance frameworks ensuring 99.9% accuracy in claims data processing and automated regulatory compliance reporting systems.

Developed advanced SQL performance optimization strategies for large-scale insurance databases, improving query execution performance by 60% and reducing system resource utilization costs.

Created comprehensive exception handling and automated error logging systems for ETL pipelines, ensuring data processing integrity and facilitating rapid issue identification and resolution.

Implemented data governance protocols including data lineage documentation, audit trail maintenance, and access control mechanisms for sensitive insurance and customer data.

Collaborated with actuaries, underwriters, and claims processing teams to develop analytical insights supporting risk assessment methodologies and pricing strategy optimization.

EDUCATION & CREDENTIALS

Master’s in Cybersecurity University of North Texas 2025

Bachelor’s in Information Technology J B Institute of Engineering and Technology 2022

Certifications:

AWS-Certified Cloud Practitioner

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