Real-Time Data Pipeline for Insurance Claim Processing Optimization

In the competitive insurance industry, efficient claim processing is crucial for maintaining customer satisfaction and operational efficiency. Our startup is focused on revolutionizing this process by implementing a real-time data pipeline. The goal of the project is to streamline the ingestion, processing, and analysis of claims data from multiple sources. The successful candidate will design a data architecture that supports real-time analytics, providing insights for faster claim adjudication. Key technologies include Apache Kafka for event streaming, Spark for processing large datasets, Airflow for orchestrating workflows, and Snowflake or BigQuery as the data warehouse solution. The project involves setting up MLOps practices to automate machine learning model deployment and data observability to ensure data quality. By the end of the project, we expect a significant reduction in claim processing time and improved accuracy in claim assessments.