Job Description Summary

The Clinical Science Data & AI lead (CSDAL) will initiate and lead the development of data and AI strategy and activities focused on delivering value to programs in development. The CSDAL will utilize their expertise in drug development, scientific knowledge and background on the disease and therapies, and technical leadership in data science and AI to drive and lead interdisciplinary collaborations and decision making for assigned projects. Demonstrating high levels of independence in support of complex projects, they are responsible for collaborating with the clinical development team and members of the program team and across the organization more broadly, as well as identifying external partners to drive project execution leveraging external innovation and resources.

Works with the function leads and teams in Clinical Development (CD) and Global Program Teams (GPTs) in developing, leading and implementing key projects within the Data Design and Clinical Innovation (DDCI) team and cross-functionally with partners efficiently and consistently to enable Development priorities and meet compliance standards.

May serve as:

• Local manager of a small team or
• Individual contributor who is a thought leader or subject matter expert with deep technical knowledge in data science, AI and machine learning, scientific knowledge and fluency, experience with drug development and regulatory framework, stage gates and steps for advancing programs through registration.


Specifically, be the primary DDCI contact for data and AI, contribute to the data strategy, and support such projects, including hands-on computational model development and application, internalization, validation and piloting of external innovative technology, in close collaboration with internal and external stakeholders e.g. program clinical development teams, DECC, Precision Medicine, Data 42 and analytics. Drive towards a data and AI-informed clinical development organization through relevant training and workshops.

Job Description

Role Purpose

• Initiate and Lead data and AI projects in DDCI team and represent DDCI within the clinical development team

• Lead and manage a team of data scientists and analysts to drive data-driven decision-making processes

• Have a strategic mindset and the ability to align data science initiatives with broader business goals. possess a deep understanding of the organization's industry, market trends, and competitive landscape to provide insights that contribute to strategic decision-making.

• Actively lead the identification of data scientific and clinical needs in clinical development in one or more therapeutic areas, and in the development and implementation of strategic solutions to these gaps, e.g.

  • Evaluate the data quality from internal and external data sources for DDCI projects 

  • Collaborate with internal stakeholders to bring in external data to internal data platform

  • Evaluate and implement AI solutions to improve the efficiency and effectiveness of clinical development programs, including hands-on computational model development and application

  • Collaborate with data science groups to support the implementation of use cases and help identify work flows and techniques that may be reproducible

  • Bridges scientific, technical, and drug development expertise to engage with clinical leads in CD, program teams, disease units,  analytics, regulatory and commercial for data science and AI  approaches

  • Enables the evaluation, internalization, validation and piloting of novel advanced external technologies.

• Partner with Analytics and other Data Science organizations to plan and implement training and coaching in order to drive a culture of data and AI literacy and innovations to drive clinical development success.

• Track data science and AI projects within DDCI requiring inputs and support

• Scope and evaluate data science and AI technology solutions for drug development 

• Ensure data transformation and analysis specifications to ensure completeness, correctness and adherence to department guidelines and SOPs as well as to applicable GxP requirements

• Manage relationships with external vendors and partners for data-related projects.

• Mentor and develop team members, fostering a culture of continuous learning and growth.

• Communicate findings, recommendations, and insights to executive leadership and other stakeholders

Requirements:

• PhD (essential), Post Doc (desired) in data science, biostatistics, computational biology, bioengineering or related field

• Fluency in English (spoken & written)

• ≥ 10 years of involvement in clinical research or drug development in an academic or industry environment.

•  ≥ 7 years of contribution and/or leadership and accomplishment in all aspects of data science and associated applications for development programs, in a global/matrix environment in pharmaceutical industry

• Significant experience in data science, machine learning, and analytics, with a proven track record of implementing successful data strategies and delivering impactful insights

• Experience in leading and managing teams of data scientists, analysts, and other data professionals, as well as working with external partners

• Possess a strong business acumen, including a solid understanding of how data analytics can drive value and impact business outcomes. They should be able to effectively communicate data-driven insights and recommendations to non-technical stakeholders, influencing decision-making across the organization

• Excellent interpersonal and communication skills (written and verbal), presentation.

• Excellent analytical, process-oriented and data driven mind- set..

• Coach/lead people (a plus): inspire and empower others to be strong leaders.

• Demonstrated ability to establish strong scientific partnership with key stakeholders

• Thorough knowledge of GCP, clinical trial design, statistical analysis methodology, and regulatory/clinical development process

• Scientific background in basic and clinical research with good understanding and knowledge of drug development.

• Strong skills in leading and managing cross-functional projects with significant (visible) business impact.

• Proficient in Python, SAS, R, and R-shiny; Building machine learning models utilizing high performance computing (HPC) environments

• Significant experience, and proven ability to effectively engage, manage and influence associates from widely varying backgrounds & functions within a dispersed and highly matrixed organization.

Benefits and rewards: 

Read our handbook to learn about all the ways we’ll help you thrive personally and professionally: 

https://www.novartis.com/careers/benefits-rewards 

Commitment to Diversity & Inclusion:

We are committed to building an outstanding, inclusive work environment and diverse teams representative of the patients and communities we serve.

Accessibility and accommodation: 

Novartis is committed to working with and providing reasonable accommodation to all individuals. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the recruitment process, or in any order to receive more detailed information about essential functions of a position, please send an e-mail to inclusion.switzerland@novartis.com and let us know the nature of your request and your contact information. Please include the job requisition number in your message. 

Why Novartis: Helping people with disease and their families takes more than innovative science. It takes a community of smart, passionate people like you. Collaborating, supporting and inspiring each other. Combining to achieve breakthroughs that change patients’ lives. Ready to create a brighter future together? https://www.novartis.com/about/strategy/people-and-culture

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Skills Desired

Applied Mathematics, Artificial Intelligence (AI), Aws (Amazon Web Services), Big Data, Building Construction, Cloud Computing, Computer Science, Data Governance, Data Literacy, Data Management, Data Quality, Data Science, Data Strategy, Electrical Transformers, Machine Learning (Ml), Master Data Management, Professional Services, Python (Programming Language), R (Programming Language), Random Forest Algorithm, Statistical Analysis, Time Series Analysis