Data Science Supervisor

About this role

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Skills you'll use

What you'll do

• Lead the ongoing operations, maintenance, and performance evaluation of production Agentic AI engines, FastAPI/Flask services, and Python-based analytical pipelines.
• Ensure production databases and connections to enterprise systems (such as SAP, Salesforce, and Postgres) are maintained, secure, and highly optimized.
• Establish best practices for Agent Observation, Evaluation, and prompt maintenance to adapt to shifting financial processes and business rules.
• Work with cross-functional partners across our highly matrixed organization to understand both upstream inputs to, and downstream impact of, current and future operational processes.
• Align technical specifications and post-deployment modifications with business needs and enterprise security standard guidelines.
• Act as a techno-functional leader, generating ideas for process and platform improvements and ensuring data compliance standards are met.
• Provides direct supervision and leadership to team
• Strategize and prioritize responsibilities of direct reports
• Assess business opportunities and promote use of data science, analytics within domain and build internal and external resources and expertise.
• A part of the role also requires to be hands-on and working together with external and internal partners to develop, test and operationalize data science and analytical solutions as well as ensure its adoption by businesses.

Who can apply

• 6 - 8 years of AI & data science experience preferred, including 2-3 years of direct people management experience (direct people reporting)
• BTech-BE from Tier 1/2 engineering schools or MStat/MS (Math)/MA Econ/ MS Analytics/data science from Tier 1/2 schools
• Deep expertise in Google Cloud Platform (GCP) technologies, including Cloud SQL, BigQuery, and GCP Cloud Functions.
• Advanced proficiency in Python (specifically FastAPI, Flask) and SQL.
• Direct experience with Agentic AI architectures, Prompt Engineering, Agent Evaluation, and Agent Observation.
• Strong knowledge of containerization and orchestration using Kubernetes.
• Experience integrating and maintaining connections to enterprise databases and applications like Postgres, SAP, and Salesforce.
• Design ML/LLM pipelines, good knowledge of RAG, prompt engineering.
• Monitor system performance, logs, retrieval quality and prompt-effectiveness
• Integrate microservices with ApigeeX for API management, security (authentication, authorization, rate limiting), monitoring, and analytics.

About Cardinal Health

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