Power Bi Data Analyst

Hetansh Parasbhai Shah

New York, USA +1-864-***-**** **********@*****.*** LinkedIn

PROFESSIONAL SUMMARY

Experienced Data Analyst with a track record in optimizing data pipelines and interactive dashboards to drive actionable insights. Reduced processing time by 40% and enhanced decision-making speed by 65% using advanced ETL and predictive models. Proficient in Python, SQL, and statistical techniques, with experience applying ML methods to risk assessment. Aims to leverage expertise in quantitative model validation and data-driven enhancements to improve fraud and compliance outcomes. TECHNICAL SKILLS

• Data Visualization & Reporting: Tableau, Power BI, Looker, Power Query, PivotTables, Advanced Excel Functions, KPI Dashboards, Automated Dashboards

• Programming & Analysis: Python, R, SQL, T-SQL, PL/SQL, Exploratory Data Analysis (EDA), A/B Testing

• Database, ETL & Cloud: PostgreSQL, SQL Server, Oracle, Azure Data Lake, AWS Glue, Microsoft Azure, AWS

• DevOps & Automation: GitHub, Jenkins, CI/CD, Pipelines, ETL Pipelines, Automated Deployment

• Data Integration & Workflow: Apache NiFi, Databricks, Apache Airflow

• Compliance, Security & Healthcare: HIPAA, HITECH, PII/PHI, Audit Logging, Data Encryption, Masking, Compliance Reporting, Basel Norms, RBI Guidelines, HL7, FHIR, CCD, EDI (837, 835), ICD-10, CPT, DRG, SNOMED CT, EPIC, Cerner, Meditech

PROFESSIONAL EXPERIENCE

Cardinal Health Jan 2024 - Present

Data Analyst NY

• Reduced monthly claims data processing time by 40% by developing optimized ETL pipelines using Apache NiFi and Databricks on Azure, which enhanced performance for downstream analytics teams.

• Enhanced clinical decision-making speed by 65% by designing and automating interactive dashboards with Tableau, Looker, and embedded data models, enabling self-service analytics for physicians and care coordinators.

• Standardized millions of records of claims and EHR data by implementing robust transformation logic using HL7, FHIR, and CCD standards from systems such as EPIC, Cerner, and Meditech, thereby improving interoperability.

• Constructed high-performance SQL-based data pipelines using T-SQL, PL/SQL, and PostgreSQL to extract, transform, and load complex 837/835 EDI claim datasets, increasing payer-provider data exchange efficiency.

• Engineered real-time ingestion pipelines for patient encounter data using Databricks, Azure Data Lake, and Apache Airflow, enabling near real-time updates to care coordination dashboards.

• Implemented diagnosis and procedure code standardization by integrating ICD-10, CPT, DRG, and SNOMED CT code sets across datasets, facilitating consistent clinical analytics and reporting.

• Developed Excel-based reporting dashboards with Power Query, PivotTables, and VBA scripting for operations and claims teams, streamlining audit workflows and reducing manual errors by 30%.

• Ensured full HIPAA and HITECH compliance by applying PII/PHI masking, data encryption, and automated audit trail logging across analytics pipelines and reporting environments.

• Automated the deployment of analytics assets by utilizing GitHub for version control and establishing CI/CD pipelines in Jenkins, supporting seamless delivery of notebooks, ETL jobs, and dashboards across dev, test, and prod environments. Zensar Technologies Apr 2020 - Dec 2022

Data Analyst India

• Automated a data pipeline using Python and AWS Glue, reducing data processing time by 40% and improving operational efficiency.

• Developed dynamic and interactive dashboards with Power BI, resulting in a 30% increase in stakeholder engagement and empowering data-driven decision-making across various financial departments.

• Conducted rigorous A/B testing on loan approval processes, achieving a 20% increase in approval rates while maintaining stringent controls to ensure stable default risk levels.

• Performed comprehensive exploratory data analysis to uncover actionable insights and trends within financial datasets, supporting strategic planning and risk assessment.

• Constructed advanced predictive models employing logistic regression and random forest algorithms to accurately assess and quantify credit risk, thereby informing lending strategies.

• Designed and automated real-time financial dashboards that visualized critical key performance indicators (KPIs), providing stakeholders with immediate access to performance metrics and insights.

• Optimized SQL queries through advanced techniques, enhancing query performance by 35% and significantly improving data retrieval times and overall database efficiency.

• Leveraged advanced Excel functions and macros to automate repetitive financial reporting tasks, increasing accuracy and reducing manual workload.

• Developed and deployed time series forecasting models to predict future financial trends, enabling proactive decision-making and strategic financial planning.

EDUCATION

State University of New York at New Paltz

Master of Computer Science

Ahmedabad Institute of Technology

Bachelor of Computer Engineering

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