Data Science Lead

About Cardinal Health

Cardinal Health, Inc., headquartered in Dublin, Ohio, is a leading global healthcare services and products company that connects patients, providers, payers, pharmacists, and manufacturers for comprehensive care coordination. With nearly a century of experience and over 50,000 employees across almost 60 countries, Cardinal Health ranks among the top 20 of the Fortune 500. The Bangalore Innovation and Global Capability Centre (GCC), established in 2021, supports various business areas through Enterprise IT, Commercial Technologies, and Business Process Solutions.

Team Overview

The AI & Data Science team develops analytics and AI solutions to enable Cardinal Health to achieve cost savings, efficiency gains, and revenue growth. They focus on driving innovation by implementing cutting-edge technologies that deliver unique business advantages.

Role Summary

The Data Science Lead will supervise the post-deployment phase and ongoing optimization of Agentic AI and Intelligent Automation tools within the Finance Digital Solutions portfolio. This role ensures the operational reliability, security, and performance of generative AI agents, large language model integrations, and production workflows. Close collaboration with both onshore and offshore developers, data scientists, and business stakeholders is required to manage risks, troubleshoot complex issues, and maintain critical solutions long-term.

Key Responsibilities

• Manage the continuous operation, maintenance, and performance assessment of production Agentic AI engines, FastAPI/Flask services, and Python-based data pipelines.
• Maintain secure and optimized production databases and their connections to enterprise systems like SAP, Salesforce, and Postgres.
• Develop best practices for monitoring Agentic AI performance and updating prompts to reflect evolving financial processes and rules.
• Collaborate extensively across the organization to understand the inputs and impacts of operational processes.
• Ensure alignment of technical modifications with business needs and enterprise security policies.
• Lead and mentor team members, prioritizing their tasks and guiding their professional growth.
• Drive the adoption of data science and analytics, identifying new business prospects within the domain and expanding internal and external expertise.
• Engage hands-on with internal and external teams to develop, test, and deploy data science and analytical solutions, facilitating business adoption.
• Leverage diverse data types—including transactional, big data, and structured/unstructured sources—to develop impactful analytic solutions.

Required Qualifications

• 7 to 12 years of experience in AI and data science, including 2 to 3 years in a people management role.
• B.Tech/B.E. from Tier 1 or 2 engineering institutes, or MStat, MS Analytics, MA Economics, or related degrees from reputed institutions.
• Strong expertise in Google Cloud Platform (GCP) services such as Cloud SQL, BigQuery, and Cloud Functions.
• Advanced skills in Python, especially FastAPI and Flask frameworks, along with SQL proficiency.
• Experience with Agentic AI architectures, including prompt engineering, evaluation, and observation.
• Knowledge of containerization and orchestration tools, especially Kubernetes.
• Proven ability to integrate and maintain connections with enterprise applications like Postgres, SAP, and Salesforce.
• Familiarity with designing ML and LLM pipelines, including knowledge of retrieval-augmented generation (RAG) and prompt engineering.
• Skill in monitoring system performance, logs, retrieval accuracy, and prompt effectiveness.
• Experience integrating microservices with API management platforms such as ApigeeX, including security features like authentication, authorization, and rate limiting.
• Competency in AI domains including Agentic AI, Generative AI, optimization techniques, statistics, machine learning, NLP, and multimedia analytics.
• Preferably familiar with Agile and Scrum methodologies.

Soft Skills

• Strong coaching and mentoring abilities for data science operations teams.
• Excellent communication capabilities, including storytelling, presentation, and written skills.
• Highly motivated, energetic, adaptable, and able to manage multiple priorities.
• Ability to collaborate effectively with teams and stakeholders to facilitate change and analytics adoption.

Eligibility

Applications are open to candidates possessing any graduate degree.