Associate Director Data Systems & AI Enterprise Competitive Intelligence

**Job Description Summary** #LI-Hybrid Location: Hyderabad, India About The Role: Enterprise Competitive Intelligence (ECI) is responsible for gathering, assessing, organizing, and delivering timely, relevant, high-quality competitive intelligence that supports Novartis pipeline, portfolio, and strategic decision-making. As ECI moves from a service-provider model toward a strategic partnership model, the function needs scalable data systems, governed repositories, and AI-enabled workflows that make validated CI accessible, reusable, and useful across business units. In this role you will shape and govern the ECI data systems and AI agenda: building and leading the CI knowledge layer, ensuring CI data is available, searchable, API-ready and usable by AI, and enabling repeatable AI-assisted workflows that improve speed, quality, consistency and enterprise leverage. The role will act as the bridge between ECI, business-unit insights teams, Data Digital & IT (DDIT), enterprise knowledge management teams (e.g. NKC), and relevant external partners to deliver pragmatic solutions while preparing ECI for future AI-enabled ways of working.   **Job Description** **Key Responsibilities:** **Strategic Vision and Roadmap** * Drive the ECI Data Systems and AI vision, roadmap and delivery plan, aligned to ECI priorities, Novartis business-unit needs and enterprise technology direction. * Translate ECI’s ambition for a single, trusted CI knowledge layer into sequenced initiatives, milestones, governance forums and investment decisions. * Maintain a balanced build/buy/partner perspective, evaluating whether capabilities should be built internally, sourced from vendors, or co-developed with partners. * Represent Data Systems and AI on the ECI Leadership Team and support ECI Steering Committee discussions on AI, repositories, data governance, interoperability, prioritization and funding. **CI Repository and Knowledge Layer** * Lead the design and implementation of the ECI repository / knowledge layer, consolidating curated CI outputs and enabling clear navigation across TAs, business units, congress outputs, Strategic CI, and other CI domains. * Ensure CI data and outputs are findable, reusable, appropriately tagged and governed, including metadata, taxonomy, ownership, access rights and archival rules * Drive interoperability with key enterprise and business-unit systems * Ensure the repository is not only a document store, but evolves toward an AI-ready data product that can be consumed by humans, AI agents and other approved enterprise applications. **AI-Enabled Workflows and Automation** * Identify, prioritize and deliver AI-assisted workflows that reduce manual effort and improve quality in recurring ECI activities * Develop reusable templates, prompts, workflow patterns and validation checkpoints that ECI associates can apply consistently across therapeutic areas and business-unit requests. * Partner with ECI leaders and specialists to define future-state workflows before tool selection, ensuring AI augments expert judgement rather than replacing critical CI interpretation. * Support pilots and MVPs over validated CI content and potential CI agent capabilities anchored in governed internal data. **Governance, Quality and Access Management** * Establish data governance standards for CI assets, including lineage, ownership, lifecycle, metadata, access policies, quality checks and decision rights. * Ensure CI data is accurate, current, appropriately curated and protected, with expert oversight and clear escalation routes for sensitive or uncertain content. * Coordinate access management across ECI, insights teams and broader approved user groups, balancing enterprise accessibility with confidentiality, compliance and business-unit needs. * Work with Legal, ERC, DDIT, knowledge-management teams and business owners to ensure AI-enabled CI workflows comply with Novartis policies, privacy, security and responsible AI expectations. **Stakeholder Engagement and Enterprise Partnership** * Serve as the primary ECI interface for data systems and AI topics with business-unit CI / insights leaders, ECI TA Leads, Strategic CI, DDIT, NKC, and other platform owners * Build alignment across stakeholders on data standards, workflow priorities, repository design, access model, change-management needs and success measures. * Create feedback loops with end users to ensure systems and AI workflows improve usability, relevance, trust and adoption across ECI and its stakeholders. * Actively promote cross-BU reuse of CI outputs and reduce duplication by making the right intelligence easier to find, compare and apply. **Delivery, Vendor and Financial Discipline** * Run a lightweight but rigorous delivery model across Data Systems and AI workstreams, including backlog management, MVP demos, milestone tracking, dependency management and risk escalation. * Evaluate and manage vendors and pilots in the AI for CI space, including clarity on expected value, data requirements, procurement implications, integration feasibility and exit criteria. * Manage the Data Systems and AI budget / project spend once approved, supporting timely forecasting, vendor decisions and efficient allocation of scarce resources. * Help ECI leadership make transparent trade-offs across repository build, AI workflow development, vendor pilots, external data feeds and internal technical capacity. **Talent, Capability Building and Change Management** * Build ECI capability in data systems, AI literacy, prompt/skill development, responsible AI use and data governance fundamentals. * Lead or coordinate a small expert pod/matrix team of data systems, AI, repository and workflow specialists as the book of work evolves; this may evolve into a small team of direct reports * Develop onboarding, guidance, playbooks and training that help ECI associates adopt new ways of working and confidently use AI-enabled workflows against validated CI content. * Support change-management communication so stakeholders understand what is changing, why it matters, and how to engage with the new repository and AI-enabled capabilities. **Results Orientation and Continuous Improvement** * Deliver measurable improvements in accessibility, reuse, speed, quality and scalability of ECI outputs. * Use adoption analytics, user feedback, data quality indicators and workflow performance metrics to iterate rapidly and course-correct. * Maintain a pragmatic “start now, evolve over time” mindset while preserving a clear target architecture for an AI-ready, enterprise CI capability. * Ensure Data Systems and AI work continually strengthens ECI’s position as a trusted, proactive strategic partner to the enterprise. **Essential Requirements:** * Advanced degree or equivalent experience in life sciences, data science, computer science, engineering, healthcare analytics, business technology, or related field; PhD / MBA / MSc or equivalent experience desirable. * ≥12yrs experience with demonstrated ability to bridge business and technical teams: able to understand CI needs, translate them into data / AI requirements, and work effectively with IT, data science, vendors and senior stakeholders. * Strong understanding of data systems, knowledge management, metadata / taxonomy, data governance, search, APIs, RAG / knowledge-layer concepts, workflow automation and AI-enabled productivity tools. * Experience delivering digital products or data platforms through MVPs, agile delivery, stakeholder feedback, adoption tracking and iterative improvement. * Excellent judgement on data quality, responsible AI, information security, access management, compliance and vendor / partner management. * Strong stakeholder-management skills, with ability to influence across a matrix and engage senior leaders while remaining pragmatic and delivery-oriented. * Curiosity, energy and change leadership mindset; comfortable working in ambiguity and building new capabilities while maintaining business continuity. * Excellent oral and written English communication skills; able to explain technical choices in simple, business-relevant language. * People leadership or matrix leadership experience preferred, including coaching technical and non-technical colleagues through new ways of working   **Skills Desired** Cross-Functional Collaboration, Customer Engagement, Customer Insights, Data Analytics, Digital Marketing, Market Research, Media Campaigns, Product Marketing, Stakeholder Engagement, Stakeholder Management, Team Leadership, Waterfall Model