Sr. Principal Data Scientist / Clinical Director I, Data and AI Convergence

Purpose:

The Director, Clinical Data and AI Convergence, will serve as the physician leader within AbbVie’s R&D Convergence Core Team, responsible for identifying and executing opportunities where data convergence, advanced analytics, and AI technologies can transform strategic decision-making processes and optimize end-to-end clinical and translational medicine workflows. This role brings together deep medical expertise, strategic vision, and applied data science capabilities to develop integrated, scalable workflow solutions - moving beyond isolated point tools - to accelerate trial execution, improve decision quality, and enhance operational efficiency across AbbVie’s therapeutic portfolio. The Director will

• Act as the principal clinical integration authority for Convergence initiatives, ensuring solutions are clinically relevant, scientifically rigorous, operationally feasible, and compliant with regulatory standards.
• Lead efforts to assess existing workflows, identify systemic gaps, and collaborate with teams to architect advanced analytical and AI-enabled processes that seamlessly embed into R&D processes, from early research through late-stage development.
• Ensure that clinical workflow innovations create measurable value for AbbVie’s pipeline and shape a sustainable foundation for enterprise-wide adoption of advanced data capabilities

Responsibilities:

 

Strategic Workflow Integration & Clinical Leadership

• Serve as the primary clinical voice within the Convergence Data and AI team, ensuring initiatives address real-world medical and operational needs.
• Translate therapeutic area and functional priorities into integrated workflow solutions that can scale across programs and indications.
• Partner across R&D to identify workflow inefficiencies, bottlenecks, and decision-making gaps that can be addressed through end-to-end data convergence and advanced technological strategies.

 

Design & Implementation of Integrated Solutions

• Lead the collaborative development of architecture and enterprise level workflows integrating diverse data sources into unified, analytics-ready frameworks.
• Ensure new workflows are interoperable, user centric, and aligned with trial governance, decision forums, and change management plans.
• Oversee the clinical validation of AI derived outputs for patient selection, endpoint strategies, trial optimization, safety surveillance, and benefit–risk assessment

 

Cross Functional Collaboration & Change Enablement

• Facilitate co-creation of solutions with clinicians, data scientists, biostatisticians, operations leaders, and regulatory partners.
• Champion cultural adoption of integrated data and AI workflows through stakeholder engagement, targeted training, and transparent demonstration of business/clinical impact.
• Disseminate lessons learned, best practices, and standardized methodologies across functions and therapeutic areas to accelerate adoption

*Role can be hired at Sr. Principal Data Scientist OR Clinical Director I depending on years of experience and education*

Qualifications for Clinical Director I:

• MD with 8-10 years of pharmaceutical/biotech industry experience in clinical development or translational medicine; substantial experience in data enabled workflow transformation.
• Deep understanding of the entire clinical development lifecycle, including trial design, execution, regulatory submission, and post-approval processes.
• Proven success in leading enterprise level workflow transformations integrating AI, advanced analytics, or digital capabilities into regulated clinical operations.
• Strong grasp of therapeutic area variability, patient population considerations, endpoint development, and safety signal interpretation.
• Exceptional ability to translate between clinical, technical, and operational perspectives for diverse audiences.
• Demonstrated skill in influencing across matrixed organizations.

Preferred

• Board certification in relevant specialty; recent or ongoing clinical practice experience.
• in translational medicine, biomarker strategy, or precision medicine.
• knowledge of machine learning, predictive modeling, and statistical methodologies relevant to clinical research.
• with clinical data standards (e.g., CDISC) and interoperability frameworks.
• implementing change management for new workflows or technologies in clinical organizations.

• Knowledge of cloud computing platforms, big data architectures, and enterprise data integration

 

Qualifications for Sr. Principal Data Scientist:

• PhD in Computer Science, Statistics, Bioinformatics, Computational Biology, Applied Mathematics, Data Science, or related quantitative field strongly preferred; Master's degree with exceptional demonstrated expertise and extensive experience considered
• 8-10+ years of progressive experience building, deploying, and scaling advanced AI/ML solutions in enterprise environments, with demonstrated leadership of large-scale, cross-functional data and analytics initiatives.
• Proven track record of leading enterprise-wide workflow projects that resulted in measurable organizational impact and sustainable capability development
• Minimum 5+ years of experience working in highly matrixed, complex organizational environments (Preferred experience in Consulting across pharmaceutical, biotech, healthcare, or similarly regulated industries strongly preferred)

Technical Expertise

• Expert-level proficiency in advanced machine learning and artificial intelligence, including deep learning, neural network architectures, ensemble methods, transfer learning, and generative AI technologies
• Demonstrated mastery of ML/AI frameworks and platforms (e.g., TensorFlow, PyTorch, Scikit-learn, Hugging Face) and their application to complex, real-world problems
• Advanced programming capabilities in Python and R, with strong software engineering principles; experience with production code development, version control, CI/CD pipelines, and testing frameworks
• Deep understanding of MLOps principles, model lifecycle management, workflow orchestration tools (e.g., Airflow, Kubeflow, MLflow), and enterprise deployment architectures
• Experience with cloud computing platforms (AWS, Azure, others) and distributed computing frameworks for large-scale data processing and model training
• Strong expertise in data architecture, data integration patterns, and modern data platforms supporting enterprise analytics

Strategic & Leadership Capabilities

• Demonstrated success leading enterprise-scale initiatives that transform organizational workflows and decision-making processes through data and AI integration
• Proven ability to influence senior leadership, build cross-functional coalitions, and drive adoption of complex technical solutions across large, matrixed organizations
• Strong change management acumen and experience driving organizational transformation in regulated environments

• Track record of successful collaboration with multidisciplinary teams including data scientists, software engineers, clinicians, scientists, and business stakeholders

Domain Knowledge

• Experience in pharmaceutical R&D, clinical development, or healthcare analytics strongly preferred
• Understanding of regulatory requirements, clinical trial design, drug development lifecycle, and healthcare data governance preferred
• Working knowledge of healthcare data standards (e.g., CDISC, OMOP) and FAIR data frameworks preferred