Strategic purpose of this role is to organize Novartis data, make it easily accessible, and useful to authorized roles. This role will help drive the development and execution of Novartis’ ambition to turn data into a real strategic asset across the organization. This ambition is one of key pillars in the broader digital transformation happening at Novartis to be a ‘medicines and data science company.’ This data centric role will facilitate using data to digitize the biopharma value chain in finding right target, right tissue, right safety, right patients, and right commercial potential and to optimize Omni channel stakeholder experience and engagement.
More specifically, the purpose of this role is to drive, in partnership Digital Data Science and AI teams, over 10+ business units, Technology partners (internal and external) adoption of consistent framework, processes, architecture and supporting tools for analytics needs. This role will help create high quality data assets to enable analytics using data across all bio pharma data domains and value chain; omics, compounds, diseases, patients, payers, providers, sites, trials, KOLs, HCPs, EMR, EHR, patient journeys, employees, contracts, vendors, products, etc.
This role will directly report and work with the Head of Data Strategy in the Group Digital Office.
The ideal candidate will
• Exercise clear and informed decision-making using process transparent to stakeholders for data related investment and creation of data assets for all units and functions. Bringing people together who should talk to each other. Keeping in touch with every data science and analytics stakeholder regularly. Facilitating meetings for the senior stakeholders & teams (preparing, moderation and post processing). Holding retrospectives to refine approach.
• Escalation point for data related product and service owner & working groups across master data management, data engineering with governance, and information modelling. Mediating the general conflict of goals between teams (technical quality) and product owner (more features).
• Champion and build awareness and value of Data Science Enablement capabilities. Assess Data Science Enablement maturity. Organizing exchange events like Open Spaces or World Cafés for the team, its stakeholders, and its organization.
• Drive organic adoption of the capabilities, helps conducts investment planning by utilizing common Data Science Enablement Capabilities. Sharing insights throughout the company (micro-blogging, blogging, internal conferences, etc.).
• Align appropriate BU capabilities to Enterprise-level efforts. Drive continuous feedback in product management and svc ownership
• Refine the Novartis reference Data Science Enablement model and keep it update. Develop service catalog in collaboration functions and ensure alignment of projects to avoid gaps or duplication of effort. Drive key projects (lighthouses) towards using common Data Science Enablement services.
• Drive strategy and implementation product and services to enable analytics
• Drive all data domain maturity and related data services to enable Visualization, Descriptive, Inquisitive, Predictive & Cognitive Analytics and Robotics Automation.
• Define services to manage usage license, cataloging, search discovery, machine learning readiness, provenance, etc. Optimize data licensing across the Firm.
• In alignment with business needs, identify new strategic data sources and data-related collaboration opportunities. Assess value of internal and external data for acquisition/licensing and monetization (data as an asset). Coordinate and align external data engagements, initiatives, and standards.
• Evolve Novartis data transparency and data sharing strategy. Support BD&L and M&A from data perspective. Identify and leverage opportunities to replace primary data collection with secondary data.
• Develop strategy and engagement models for a patient-centric data future. Communicate Novartis data activities to the external health data ecosystem.
• Promoting cultural change
• Drive development and implementation of a change management concept in close collaboration with HR and closely aligned with the overall Novartis digital transformation to build a more data-centered mindset, incl., capability building, change agents, talent placement and more inspired, empowered, unbureaucratic organization. Create a curious, continuously learning (from successes and failures) environment.
• Develop operating model to make the business truly own and appreciate the value of the data. Define metric to measure success on becoming a more data-centric organization.
• Develop an environment which fosters a high-performance and innovative organization. Drive engagement/collaboration in a matrix organization, fostering strong partnerships – internal and external, and helping build diverse teams.
Why consider Novartis?
750 million. That is how many lives our products touch. And while we’re proud of that fact, in this world of digital and technological transformation, we must also ask ourselves this: how can we continue to improve and extend even more people’s lives?
We believe the answers are found when curious, courageous and collaborative people like you are brought together in an inspiring environment. Where you’re given opportunities to explore the power of digital and data. Where you’re empowered to risk failure by taking smart risks, and where you’re surrounded by people who share your determination to tackle the world’s toughest medical challenges.
10 + experience in data management and data strategy in industry
Hands on experience with managing Data Science Enablement related activities across many of biopharma data domains e.g. omics, compounds, diseases, patients, payers, CROs, sites, trials, KOLs, HCPs, EMR, EHR, claims, patient journeys, employees, contracts, vendors, products, etc.
Demonstrated leadership of use case based agile implementation of data strategy in cross-organizational and cross-functional teams.
Proven track record in implementing a Data Science Enablement program from scratch in Pharma or other multinational, multi-business organizations
Skills on capabilities - Manage the build out of following digital data management capabilities
General understanding of data driven target identification and links between target and disease, differentiated efficacy, availability and predictive nature of biomarkers.
General understanding of data driven tissue identification towards adequate bioavailability and tissue exposure, definitions of PD biomarkers, preclinical and clinical PK/PD and target liability
General understanding of data driven Safety Analytics towards differentiated and clear safety margins, secondary pharmacology risk, reactive metabolites, genotoxicity, drug-drug interactions, and target liability
General understanding of protocol design and data driven Patients Analytics to identify most responsive population, risk-benefit for given population
General understanding of data driven commercial potential for differentiated value proposition verses future standard of care, focus on market access, drivers of regulatory compliant omnichannel engagement and experiences with patients, payer and provider. Understand personalized healthcare strategy, digital medicines, including diagnostic and biomarkers.
Advance knowledge of data Visualization tools and techniques. Expertise in Descriptive, Inquisitive, and Predictive analytics. Working knowledge of Cognitive Analytics and Robotics Automation. Deep understanding if data science workflow and productivity issues related to data availability, quality and productionizing data science. Ability to code in R and/or Python.
Data Distribution capability through APIs for Apps to Analysts to semantically search and find data assets without needing to understand exactly where it is physically stored and maintained.
Semantically curated Data APIs to enable complex data API Mashups without user side code. Enable smart Applications, Portals, End Users, Business Intelligence, Analytics, Reports, Dashboards, OLTP, Compliance, B2B, Semantic Browsers, etc.
Analyze and Act enablement capabilities to support simple reporting (descriptive analytics) to advance Assist and Suggest type AI capabilities to help improve the performance and productivity of our decision makers in optimizing our core business processes for Right target, right tissue, right safety, right patients, right commercial potential and optimized stakeholder engagement
Security and Access capability to prevent unauthorized access, use, disclosure, disruption, modification, inspection, recording or destruction of information
Send an expression of interest and CV to the listed contact.