Clinical Director, Clinical Data and AI Convergence

About the role

The Clinical 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.

Responsibilities

• 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

Requirements

• Medical Doctor (M.D.), Doctor of Osteopathy (D.O.) or non-US equivalent of M.D. 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.

Qualifications

• 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.
• Experience 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.

Skills

• Expert-level proficiency in advanced machine learning and artificial intelligence, including deep learning, neural network architectures, ensemble methods, transfer learning, and generative AI technologies.
• 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.

Benefits

Comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k).

Pay

$182,000 - $346,000 USD

Schedule

Hybrid