Head of Data Science

Key Responsibilities Leadership & Strategy Lead and mentor 200–250+ member data science, ML engineering, and analytics organization Define enterprise AI/ML vision, roadmap, and best practices Drive AI adoption across products, platforms, and business units Partner with CXOs, product heads, and business stakeholders Hands-on AI / ML Stay hands-on with model design, feature engineering, evaluation, and deployment Build and review solutions involving: Predictive & prescriptive analytics NLP, Computer Vision, Deep Learning MLOps and model lifecycle management Ensure models are production-ready, scalable, and explainable Databricks & Platform Engineering Architect and implement AI/ML pipelines on Databricks (Spark, MLflow, Delta Lake) Optimize large-scale data processing and model training Collaborate with cloud and data engineering teams Middleware & Integration Work closely with middleware teams to: Integrate ML services via APIs / microservices Enable real-time & batch model consumption Ensure secure, scalable communication between applications, data platforms, and AI services Understand middleware tools (Kafka, API Gateways, ESB, message queues, etc.) Healthcare / Insurance Focus Apply AI to use cases such as: Claims processing & fraud detection Risk scoring & underwriting Patient/member analytics Operational optimization & compliance Software Development Practices Embed AI into enterprise software development lifecycle (SDLC) Promote Agile, CI/CD, DevOps, and MLOps practices Ensure high code quality, documentation, and governance