Manager Data Science

Job Description Summary The Insights and Decision Science (IDS) team is dedicated to enabling improved decision-making at Novartis by leveraging data and advanced analytics capabilities to generate actionable insights that drive business growth. We collaborate closely with the US business, bringing insights and challenging ideas to empower smarter, data-driven decision-making. The Gen AI team pioneers enterprise-scale Generative AI solutions, specializing in building production-ready LLM systems, multi-modal AI architectures, and sophisticated agentic workflows. We leverage cloud-native GenAI platforms (AWS Bedrock, Azure OpenAI) to deliver innovative solutions that transform unstructured data into actionable insights through advanced RAG systems, multi-agent orchestration, and vision-language models. Our team excels at rapid prototyping and delivery of cutting-edge GenAI applications while implementing robust evaluation frameworks, guardrails, and responsible AI practices to ensure scalable, ethical deployments across the organization.This role is crucial for pioneering the safe and effective deployment of autonomous AI agents that can transform business operations while maintaining robust guardrails and evaluation frameworks. The Manager combines deep technical expertise in agentic AI with strategic leadership to ensure these powerful systems deliver measurable business value without compromising safety, ethics, or reliability. As organizations move beyond basic GenAI applications toward autonomous agents that can reason, plan, and execute complex tasks, this role's unique blend of hands-on technical skills and evaluation expertise becomes essential for navigating the opportunities and risks of advanced AI systems.Job Description Data Science Manager Location – Hyderabad #LI Hybrid    Major Responsibilities: · Lead the design and implementation of sophisticated agentic AI systems, including multi-agent orchestration and autonomous workflows. Define architectural standards for agent development, including tool integration, memory management, and inter-agent communication protocols · Establish comprehensive evaluation frameworks for agentic systems, measuring task completion, reasoning quality, and safety compliance. Design and implement guardrails for autonomous agents, including behavioural boundaries, output validation, and fallback mechanisms · Drive hands-on prototyping of complex agent systems while providing technical oversight to development teams. Create testing methodologies for agent reliability, including edge case handling, adversarial testing, and performance benchmarking · Balance technical depth with strategic thinking to identify where agentic AI can transform business processes. Lead technical reviews of agent architectures, personally debugging complex multi-agent interaction issues · Deep technical knowledge of agent evaluation metrics: task success rates, reasoning traces, tool-use efficiency, and safety violations. Proven experience implementing production guardrails: content filtering, action limitations, human-in-the-loop systems · Strong understanding of agent architectures: ReAct, Plan-and-Execute, Reflexion, and emerging patterns. Experience with agent memory systems: episodic memory, semantic memory, and working memory implementations · Ability to code review and debug complex agent behaviors, including emergent properties and unexpected interactions. Track record of building teams while maintaining hands-on technical involvement Minimum Requirements: Education (minimum/desirable): Master's degree in relevant field required; MBA or PhD preferred · 7+ years in AI/ML with maximum 3 years in generative AI and demonstrated expertise in agentic systems. Hands-on coding experience with complex agentic AI implementations, including multi-agent systems and tool-use agents. · Ability to balance operational execution with high-level strategic thinking, driving both immediate results and long-term GenAI transformation · Strong capability to work collaboratively with cross-functional teams, including Marketing, Field & Sales, Data Enablement & Platform Teams to ensure GenAI solutions meet business needs · Excellent communication skills, capable of effectively collaborating with senior leadership and board members on AI strategy · Ability to thrive in a fast-paced, dynamic environment and lead teams through changing business needs and priorities. Hands-on experience with agent observability and monitoring systems · Deep understanding of safety considerations for autonomous agents, including alignment techniques. Experience evaluating and implementing third-party agent frameworks and platforms · Track record of defining guardrail strategies that balance capability with safety. Published work or open-source contributions in agentic AI space preferred Why Novartis: Our purpose is to reimagine medicine to improve and extend people's lives and our vision is to become the most valued and trusted medicines company in the world. How can we achieve this? With our people. It is our associates that drive us each day to reach our ambitions. Be a part of this mission and join us Learn more here: receive: You can find everything you need to know about our benefits and rewards in the Novartis Life Handbook. to Diversity and Inclusion:  Novartis is committed to building an outstanding, inclusive work environment and diverse teams' representative of the patients and communities we serve.   Join our Novartis Network: If this role is not suitable to your experience or career goals but you wish to stay connected to hear more about Novartis and our career opportunities, join the Novartis Network here: Skills Desired Apache Hadoop, Applied Mathematics, Big Data, Curiosity, Data Governance, Data Literacy, Data Management, Data Quality, Data Science, Data Strategy, Data Visualization, Deep Learning, Machine Learning (Ml), Machine Learning Algorithms, Master Data Management, Proteomics, Python (Programming Language), R (Programming Language), Statistical Modeling