ML Solutions: Develop and deploy predictive models for risk scoring, claims automation, fraud detection, and personalization.
Backend Services: Build robust APIs using Java or Kotlin (Spring Boot or Ktor) to serve ML models and integrate with insurance platforms.
Data Pipelines: Design and optimize ETL/ML workflows in Databricks or Spark, ensuring compliance with data governance and regulatory standards.
Frontend Development: Create intuitive React.js dashboards for underwriters, claims teams, and business stakeholders to visualize model outputs and KPIs.
Database Management: Maintain PostgreSQL databases to store policy, claims, and model metadata securely.
Model Deployment & Monitoring: Implement production-grade deployment strategies with drift detection, audit trails, and rollback mechanisms.
Compliance & Security: Ensure solutions adhere to insurance regulations (e.g., MAS, GDPR) and internal security policies.
Collaboration: Work closely with actuaries, data scientists, and business stakeholders to translate requirements into technical solutions.
