Apr 2024 – Jul 2025 · 1 yr 3 mos · Mumbai, Maharashtra, India · On-site

• Led the design and implementation of a Generative AI solution to automate the U.S. medical coding process
• Achieved 95% coding accuracy, significantly improving overall quality
• Reduced manual coder effort by 60%, enhancing operational efficiency
• Integrated AI/ML models into the existing medical billing cycle, ensuring seamless adoption
• Collaborated with cross-functional teams to integrate AI/ML solutions into the existing revenue cycle management (RCM) system of the U.S. medical billing process; identified key business challenges and opportunities, and translated them into actionable data science projects
• Drove innovation by aligning AI capabilities with healthcare compliance and workflow needs
• Contributed to scalable automation in healthcare operations, showcasing the potential of AI in solving industry-specific challenges
• Designed and deployed scalable data pipelines for processing large volumes of medical records, ensuring data integrity and compliance with healthcare regulations.
• Mentoring junior data scientists, fostering a culture of knowledge sharing and continuous learning within the team to enhance overall capabilities and performance.

Aug 2021 – Apr 2024 · 2 yrs 8 mos · Hyderabad, Telangana, India · On-site

• Spearheaded creating and optimizing a GenAI model for extracting key entities from remittance and invoice documents, boosting extraction accuracy by 35-40% and significantly enhancing financial data processing efficiency.
• Developed an end-to-end pipeline for the Financial Document Scanner product using Tesseract OCR for image-based PDFs and PDFMiner for text-based PDFs.
• Extracted and organized tabular regions (e.g., balance sheets, cash flow statements, income statements) from financial statements, enabling over 90% accuracy in customer credit risk analysis across 500+ financial statements.
• Conducted exploratory data analysis (EDA) to uncover trends and patterns in complex datasets, supporting strategic decision-making and operational improvements.
• Implemented regression models to forecast payment dates for open invoices, adapting models to capture regional and subsidiary-specific trends.
• Scaled the Payment Date Prediction Model to handle 12M+ invoices across multiple regions, improving accuracy to 89%.
• Successfully led end-to-end development and optimization initiatives across data extraction, modeling, and deployment processes.