Band

Level 6

Job Description Summary

#LI-Remote

This role will be part of the Real-World Evidence team and will support the development, implementation, and operationalization of scalable real-world data platforms that enable high-quality, timely, and strategically relevant evidence generation. The Director will help advance connected data capabilities across claims, electronic health records, registries, specialty data sources, and other fit-for-purpose data assets to support priority evidence needs across the portfolio.

The Director will partner closely with HEOR leads, medical strategy teams, data partners, RWE colleagues, and cross-functional stakeholders to ensure that data platform capabilities are aligned with evidence generation priorities. This includes supporting the development of linked longitudinal data capabilities, helping evaluate and onboard data sources, strengthening data quality and documentation standards, and enabling more efficient activation of data assets for priority research questions.

As a member of the RWE team, the Director will contribute to evidence generation planning and execution by helping translate strategic evidence needs into practical data platform requirements. The role requires strong collaboration, technical knowledge of real-world data, and the ability to work across internal and external partners to support high-impact RWE deliverables.

This position can be based remotely anywhere in the U.S. (there may be some restrictions based on legal entity). Please note that this role would not provide relocation as a result. The expectation of working hours and travel (domestic and/or international) will be defined by the hiring manager. This position will require 20% travel.

Job Description

Key Responsibilities:

• Support the development and operationalization of scalable real-world data platforms that enable efficient and high-quality RWE generation.
• Partner with RWE leads and medical strategy teams to understand evidence needs and translate them into data platform requirements.
• Support integration and use of relevant RWD sources, including claims, electronic health records, registries, specialty data, and other fit-for-purpose datasets.
• Contribute to the development of linked longitudinal data capabilities to enable robust real-world analyses and endpoints.
• Help evaluate, onboard, and manage external data vendors and platform partners in collaboration with senior team members.
• Support data quality frameworks, validation protocols, documentation standards, and governance processes for RWE platform use.
• Collaborate with analytics, epidemiology, biostatistics, medical, access, and other cross-functional partners to ensure data assets are fit for purpose.
• Contribute to RWE project execution by enabling timely access to appropriate data assets and supporting efficient study activation.
• Identify opportunities to improve data platform usability, scalability, and efficiency for evidence generation.
• Communicate data platform capabilities, limitations, and opportunities clearly to internal stakeholders.
• Support development of materials, summaries, and recommendations for leadership discussions related to RWD platform strategy.
• Maintain awareness of evolving RWD sources, data linkage approaches, analytical platforms, and industry trends relevant to RWE.

Essential Requirements:

Education: A Bachelors degree is required. An Advanced degree in health economics, epidemiology, statistics, public health, health policy, data science, or a related field is required. Doctoral-level training or PharmD with relevant RWE, HEOR, epidemiology, or data science experience is preferred.

• 7+ years of experience in the pharmaceutical, biotechnology, healthcare, consulting, or data/analytics sector.
• Experience working with real-world data sources such as claims, electronic health records, registries, specialty pharmacy data, laboratory data, or linked datasets.
• Experience supporting RWE, HEOR, epidemiology, outcomes research, medical affairs, market access, or related evidence-generation activities.
• Experience collaborating with cross-functional teams and external data vendors or platform partners.
• Demonstrated ability to support complex projects, manage multiple priorities, and communicate technical concepts to non-technical stakeholders.
• Experience with data quality assessment, data documentation, governance processes, or fit-for-purpose data evaluation is strongly preferred.
• Strong understanding of real-world data sources and their application to evidence generation.
• Working knowledge of RWE study designs, observational research methods, and data considerations for healthcare research.
• Familiarity with data linkage, longitudinal patient journeys, endpoint development, and fit-for-purpose data assessment.
• Understanding of US healthcare data ecosystems, including payer, provider, and specialty data sources.
• Ability to partner with analytics and technical teams to support data platform development and implementation.
• Knowledge of data privacy, compliance, documentation, and governance expectations for RWE use.

Novartis Compensation Summary:

The salary for this position is expected to range between $185,500 and $344,500 per year.

The final salary offered is determined based on factors like, but not limited to, relevant skills and experience, and upon joining Novartis will be reviewed periodically. Novartis may change the published salary range based on company and market factors.

Your compensation will include a performance-based cash incentive and, depending on the level of the role, eligibility to be considered for annual equity awards.

Salary Range

$185,500.00 - $344,500.00

Skills Desired

Cross-Functional Collaboration, Data Analysis, Employee Development, Finance, Health Economics, Health Technology Assessment (HTA), Influencing Skills, Innovation, Inspirational Leadership, People Management, Pharmacoeconomics, Process Management, Product Launches, Project Management, Real World Evidence (RWE), Regulatory Compliance, Research Methodologies, Results-Oriented, Risk Management, Stakeholder Engagement, Stakeholder Management, Statistical Analysis, Value Propositions