Fnu Aishwarya
Data Analyst @Cigna Healthcare
Signup · Get unlimited contacts
WORK HISTORY
Data Analyst @Cigna Healthcare
NC, US
Partnered with cross-functional stakeholders to launch an enterprise Claims Data Accuracy Fraud Detection project, ensuring HIPAA and HL7 compliance with CMS frameworks. Consolidated payer–provider datasets into the Cigna Common Data Model, integrating EHR/EMR systems (Epic, Cerner, Allscripts) for unified analytics. Enhanced fraud detection models using SQL and Python, identifying duplicate and miscoded claims, cutting reprocessing costs by 21%. Designed predictive models for diabetes and MSK under the Chronic Disease Management initiative, improving early intervention accuracy by 17%. Collaborated with AI teams on the Patient Readmission Forecasting project using Scikit-learn and AWS Redshift, reducing readmission probability by 12%. Built Tableau and Power BI dashboards to visualize provider performance, strengthening benchmarking and improving network efficiency by 31%. Validated high-volume claims data in the Care Quality Insights project, closing preventive care gaps and improving chronic care adherence by 14%. Automated mapping validation with SQL and SSIS, improving efficiency by 35% and ensuring PHI protection. Executed ETL workflows via SSIS and Informatica to ensure data accuracy and compliance across payer–provider sources. Drove the Claims Utilization Analytics initiative to align metrics with CMS interoperability standards, enhancing transparency. Cleaned and transformed data using Python (Pandas) and SQL, improving data quality and model readiness by 28%. Conducted impact and gap analyses for inbound and outbound mappings, achieving 99.7% precision and strengthening audits. Led Agile sprint reviews and workshops, ensuring collaboration and timely delivery of Data Mapping Integration changes. Presented monthly data quality dashboards to leadership, highlighting measurable gains in accuracy, compliance, and throughput.
EDUCATION
California State University - East Bay
Master's degree, Computer Science
N M A M Institute of Technology, NITTE
B.E, Computer Science Engineering
ABOUT FNU AISHWARYA
Results-oriented Data Analyst with 3+ years of experience in risk modeling, fraud analytics, and financial performance optimization across healthcare and BFSI sectors. Adept at analyzing complex, multi-source datasets to generate actionable business insights, optimize cloud expenditure, and strengthen compliance with SOX, AML, GDPR, HIPAA, and Basel Successfully designed and implemented credit risk scoring and fraud detection models using Python, SQL, and Power BI, reducing false positives by 18% and saving over $2.4M annually. Skilled in partnering with business and compliance teams to automate AML/KYC validations, improve credit underwriting accuracy, and streamline claims analytics within cloud-enabled enterprise environments. Engineered and visualized key metrics via Power BI dashboards and DAX models, enabling leadership teams to track cost efficiency, risk exposure, and customer churn patterns in real time. Demonstrated excellence in data-driven decision-making through the development of predictive models, segmentation analytics, and spend forecasting frameworks that enhanced operational efficiency and accuracy. Strong collaborator skilled in end-to-end data lifecycle management, from data extraction and transformation to model deployment, performance monitoring, and compliance documentation.
This profile is compiled from publicly available professional sources. Unifers is not affiliated with or endorsed by LinkedIn. Request removal of this profile.