Data Analyst - Banner Health, USA - USA
(2024-04)
Led an enterprise healthcare analytics solution focused on Denial Management & Revenue Cycle Management (RCM), predicting claim denials, optimizing reimbursements, reducing revenue leakage, & improving first-pass claim acceptance rates.
- Architected scalable data transformation frameworks using dbt and SQL, integrating claims, eligibility, prior authorization, remittance, ICD-10, and CPT datasets into analytics-ready models for denial prediction and claims adjudication analytics.
- Directed data cleansing, standardization, and transformation using Python and Pandas, harmonizing payer, provider, diagnosis, procedure, and adjudication data, reducing anomalies by 24% and improving data reliability.
- Designed executive-level Power BI dashboards with advanced DAX measures, delivering insights into denial trends, reimbursement performance, payer behavior, appeals effectiveness, procedure utilization, and RCM KPIs.
- Engineered cloud-based data pipelines using AWS S3, AWS Glue, & Amazon Redshift, managing 3TB+ of healthcare claims data, automating ETL workflows, reducing query latency by 22%, & supporting HIPAA, HITECH, and CMS Interoperability compliance.
- Performed statistical analyses using ANOVA, regression, correlation analysis, and hypothesis testing to identify denial drivers, coding discrepancies, authorization gaps, reimbursement risks, and payer adjudication patterns.
- Integrated Generative AI and LLMs to automate denial classification, documentation validation, coding reviews, appeal recommendations, and claims insight generation, reducing manual effort by 18%.
- Delivered analytical reports on denial forecasts, reimbursement trends, payer scorecards, coding compliance metrics, and financial KPIs, reducing reporting turnaround time by 12% and accelerating decision-making.
- Collaborated with revenue cycle leaders, coding specialists, healthcare administrators, data engineers, and AI teams in Agile/Scrum environments, strengthening data governance, compliance, and enterprise healthcare analytics.
Data Analyst - PNC Financial Services, USA - USA
(2022-02 - 2024-03)
Spearheaded the development of a digital onboarding and KYC analytics platform, unifying customer transactions and compliance data to accelerate account activation, strengthen risk governance, and improve customer acquisition outcomes.
- Developed Python-based ETL pipelines processing 6,500+ daily onboarding and verification records, reducing processing time by 24%, improving data integrity, and accelerating customer approval workflows.
- Orchestrated scalable Apache Spark pipelines processing 450GB+ of daily customer and transaction data, enabling near real-time onboarding, monitoring, and delivering actionable compliance and risk intelligence.
- Optimized XGBoost and Logistic Regression models to enhance customer risk scoring, detect fraudulent applications, and improve risk prediction accuracy by 18%, reducing exposure to high-risk accounts.
- Streamlined regulatory reporting and data preparation using Alteryx, eliminating 35% of manual effort, generating 700+ monthly compliance reports, and improving operational efficiency for risk and audit teams.
- Implemented secure Azure Data Factory pipelines integrating hybrid cloud and on-premises environments, supporting 25+ critical data sources and ensuring reliable data delivery for KYC validation and regulatory reporting.
- Refined A/B testing frameworks and onboarding dashboards, improving customer approval rates by 16%, reducing application abandonment by 12%, and enabling data-driven business decisions.
- Executed advanced Python and SQL analytics on onboarding, fraud, and compliance trends, supporting AML, KYC, OFAC, and CDD requirements while reducing investigation turnaround time by 22%.
Data Analyst - Avnet, USA - USA
(2019-12 - 2022-01)
Pioneered end-to-end supply chain analytics and automation across procurement, inventory, logistics, and suppliers, enabling real-time visibility, S&OP alignment, KPI standardization, and executive decision intelligence across multi-region operations.
- Established SQL pipelines processing 18,000+ daily orders to analyze demand variability, forecast bias, lead-time volatility, and SKU velocity, enabling demand-supply balancing, safety stock optimization, and reduced stockout risk.
- Transformed enterprise data platform by establishing Snowflake model consolidating 350,000+ SKUs and multi-source datasets, enabling unified demand planning, inventory visibility, supplier analytics, and scalable executive reporting.
- Rationalized Talend ETL pipelines processing 1.8M+ daily supply chain events, improving data reliability by 9%, enforcing governance controls, and enabling trusted operational and financial reporting.
- Advanced SAS forecasting models using 8M+ records to identify demand volatility, supplier disruption risks, and optimize safety stock levels, improving forecast accuracy by 13%.
- Elevated Tableau dashboards tracking OTIF, Fill Rate, Forecast Accuracy, Inventory Turns, Backorder Rate, Lead Time Variability, Supplier Performance Index, improving decision speed by 25%.
- Standardized Excel-based planning workflows using Pivot Tables, Power Query, VLOOKUP, INDEX-MATCH, reducing manual effort by 18% and accelerating S&OP cycle efficiency by 30%.
- Institutionalized KPI governance and continuous improvement across supply chain, procurement, logistics, warehouse, and finance, improving OTIF by 11%, reducing inventory costs by 9%, and strengthening working capital efficiency.
