Jobs at Novartis

Field-based leader serving as primary contact for assigned accounts in autoinflammatory diseases. Develops account strategies, navigates access and reimbursement, builds cross-functional partnerships, educates stakeholders, and drives patient identification, onboarding, and long-term therapy success. Represents the company in the rare disease community and collaborates with Medical, Market Access, Patient Services, and Commercial teams.

Field-based territory sales role supporting dermatology accounts. Build strategic territory plans, resolve access challenges, drive product demand, coordinate cross-functionally, deliver patient access support, and engage customers via omni-channel outreach. Requires heavy travel and territory-based relationship management to improve patient outcomes.

Field-based regional leader for Access & Reimbursement teams supporting cardiovascular portfolio. Hire, coach, and manage regional staff; drive compliant execution of national strategies; resolve access and reimbursement hurdles; coordinate cross-functionally to support launches and patient access; manage budget, operations, and performance. Requires extensive stakeholder engagement and frequent travel.

Owns a portfolio of NovaOS capabilities from concept through delivery, adoption, and continuous improvement. Responsibilities include managing product backlogs and roadmaps, prioritizing features, defining requirements and success metrics, coordinating cross-functional engineering, AI, UX, data, and architecture teams, leading product discovery and release planning, monitoring adoption and KPIs, and ensuring alignment with product governance, architecture, and Responsible AI standards.

Leads the strategy, roadmap, and product organization for NovaOS, an enterprise AI operating system. Oversees a portfolio spanning data, semantic, agentic, and experience layers; partners with business, engineering, and technology leaders to prioritize investments and deliver measurable outcomes. Establishes product governance, lifecycle practices, success metrics, and feedback mechanisms while building and mentoring a high-performing product management team.

Design and govern conceptual, logical, and physical enterprise data models supporting analytics, reporting, AI-ready datasets, and certified data products. Translate business requirements into scalable data structures across customer, product, payer, and territory domains. Establish modeling standards, review models against Common Data Model standards, maintain metadata and lineage accuracy, and resolve data gaps and inconsistencies. Collaborate with business, engineering, and technology stakeholders to provide modeling expertise and design guidance.

Leads enterprise reporting for data quality, governance, compliance, and operational performance. Designs executive dashboards, scorecards, and reporting packages; integrates metadata and quality metrics; aligns definitions and thresholds with stakeholders; oversees incident and remediation tracking; manages vendors, schedules, documentation, and change controls; validates data integrity; automates recurring reports; and escalates risks and compliance issues to leadership.

Lead enterprise data engineering standards, governed pipelines, data contracts, observability, quality controls, lineage, testing, and automation. Partner with governance, privacy, architecture, modeling, and platform teams to deliver reliable, compliant, AI-ready data products. Monitor operational performance and resolve pipeline and data reliability issues across complex enterprise environments.

Develop and execute a rare disease data strategy for the U.S. Commercial organization. Translate business priorities into data roadmaps, establish governance and metadata standards, coordinate data sourcing and vendor evaluations, manage delivery risks and dependencies, drive adoption of new ways of working, and report progress to senior stakeholders. Ensure data strategy activities align with privacy policies and regulations while optimizing data assets, products, and lifecycle management.

Leads the strategy, architecture, development, deployment, monitoring, and optimization of an agentic AI platform. Transforms products, processes, and workflows into scalable AI-enabled capabilities; establishes standards for performance, security, governance, and reliability; evaluates models and orchestration frameworks; partners cross-functionally on technical roadmaps; and builds and mentors high-performing engineering teams.

Oversee strategic oncology data partnerships supporting US Commercial brands and business priorities. Identify data needs, evaluate vendors and data assets, monitor partnership spend and performance, and ensure data quality, privacy, security, compliance, governance, and stewardship. Collaborate with vendors, analytics teams, field enablement, access, and oncology stakeholders to resolve data issues, recommend fit-for-purpose datasets, translate business needs into data solutions, and provide advisory support on data interpretation and appropriate use.

Leads enterprise core data management by defining standards for data, metadata, modeling, and quality; driving governance adoption; and delivering trusted, AI-ready datasets. Oversees data operations, service levels, documentation, metrics, risk management, and continuous improvement. Partners with engineering, business teams, vendors, and senior stakeholders while leading and developing Associate Directors and distributed teams.

Leads strategic external data partnerships supporting customer engagement and integrated marketing. Oversees vendor performance, spend, data quality, security, compliance, governance, and integration into enterprise platforms. Establishes SLAs, manages data acquisition and stewardship, resolves quality issues, reports partnership performance to leadership, and coordinates training. Evaluates emerging data offerings, AI-enabled capabilities, and partnership models to improve marketing effectiveness, customer engagement, decision-making, and enterprise value.

Leads data strategy for Customer Engagement and Integrated Marketing across U.S. life sciences functions. Develops roadmaps, investment recommendations, data capabilities, governance, adoption plans, and success measures. Aligns business, analytics, governance, technology, procurement, data partnership, and vendor stakeholders. Manages external data partnerships and related privacy, security, quality, and compliance risks while maximizing reuse and value of enterprise data assets.

Leads the engineering strategy, architecture, development, operations, and continuous improvement of an enterprise agentic AI foundation. Establishes scalable engineering standards, operating models, governance, and reusable platform services that enable AI products and intelligent workflows. Partners with product, data, infrastructure, security, and business teams to modernize existing systems, guide cross-functional delivery, monitor operations, and communicate priorities, risks, and investment needs to senior leaders. Manages and develops product or engineering leaders while driving measurable business value.

Leads demand intake, prioritization, governance, portfolio planning, resource capacity alignment, and delivery oversight across the Data Governance and Data Management Office. Develops executive dashboards, monitors portfolio health and milestones, escalates risks and dependencies, facilitates governance forums, standardizes program-management practices, and drives continuous improvement. Partners with senior leaders and cross-functional teams to align data initiatives with business value, organizational capacity, and strategic priorities.

Leads enterprise data product strategy, roadmaps, prioritization, adoption, governance, and lifecycle management for reference data, master data, metadata, and standards. Defines reusable, AI-ready products containing business meaning, rules, metrics, lineage, and context. Partners with data enablement, technology, analytics, governance, and business teams to scale reliable products, establish standards and service expectations, measure value, resolve issues, and drive stakeholder adoption.

Coordinates technical onboarding and ongoing operations for data partners and vendors. Ensures data delivery, ingestion, metadata, catalogs, documentation, and inventories remain accurate and current. Tracks data quality, SLAs, delivery performance, operational metrics, and issue resolution across business, technical, engineering, analytics, and vendor teams. Maintains centralized issue trackers, escalates risks, translates technical problems into business impacts, and drives cross-functional follow-through in a matrixed environment.

Leads rapid design, development, and validation of agentic AI proof-of-concepts. Partners with stakeholders, product, architecture, and engineering teams to identify opportunities, build LLM-based prototypes, evaluate emerging technologies, document methodologies, and transition successful solutions into production roadmaps. The role also mentors AI engineers and supports enterprise AI innovation.

Leads the design, prototyping, and validation of AI agents and autonomous workflows. Evaluates foundation models, agent frameworks, orchestration technologies, and developer tools; creates reusable proofs of concept and reference implementations; and partners with engineering, product, platform, and architecture teams to productionize successful innovations. Establishes best practices for prompt engineering, reasoning, memory, evaluation, and observability while mentoring AI engineers and promoting experimentation.