Head of Data Biomedical Research

Major accountabilities but not limited to:

• Develop and implement comprehensive data strategies that align with business objectives and research priorities.
• Advise management on strategic direction, scope and approach.
• Promote and foster a data-driven culture, enhancing data literacy across the organization.
• Monitor and evaluate the effectiveness of data strategies, adjusting as needed to achieve desired outcomes.
• Stay informed about emerging trends and technologies in data management and apply innovative solutions to enhance data utilization.
• Establish and oversee data governance frameworks, ensuring high standards of data quality, accessibility, and compliance.
• Align on and contribute to Novartis Enterprise Data Management framework.
• Define and implement data standards, policies, and procedures, driving inoperability across systems and processes.
• Lead efforts to validate, review, and reconcile data, maintaining high-quality standards across all datasets.
• Integrate and harmonize data across multiple systems and functions, facilitating seamless data flow.
• Develop tools, workflows, and integration solutions to eliminate data silos and enhance collaboration across teams.
• Enable access to high-quality, reliable data for research and development teams to drive decision-making.
• Facilitate effective collaboration between data teams and business stakeholders, ensuring alignment with organizational goals.
• Build strong relationships with internal and external stakeholders, including external partners, to drive innovation and data-sharing opportunities.
• Communicate data strategies, insights, and recommendations to stakeholders at all levels of the organization.
• Lead a growing organization expected to reach 35+ people.

Minimum Requirements:

• PhD or master’s degree in computer science, data science, AI, machine learning, or a related discipline (preferred).
• 15+ years of experience in data strategy, management, and governance, with a demonstrated understanding of advanced data methodologies applied to drug discovery and development in the pharmaceutical/biotech industry.
• Experience leading multidisciplinary, global teams and operating successfully in matrixed, fast-paced environments.
• Proven ability to manage complex portfolios and work with diverse stakeholders to prioritize resources and meet business needs.
• Strong leadership and communication skills, with the ability to influence stakeholders and drive organizational change.
• Strategic thinker with a vision for data-driven decision-making and a strong understanding of data management, governance, and analytics.
• In addition to traditional data management skills, the ideal candidate would possess competency in the following advanced data technologies: deploying scalable data solutions on cloud-native data platforms, experience with vector databases, implementing a decentralized, domain-driven data architecture, a solid grasp of ML Ops principles including the data centric aspects of model training, deployment and monitoring, experience implementing data observability tools, and familiarity with graph databases.

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