Company Description
About AbbVie
AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas including immunology, oncology and neuroscience - and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at www.abbvie.com. Follow @abbvie on LinkedIn, Facebook, Instagram, X and YouTube.
Job Description
Purpose:
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. 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
Qualifications
- 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.
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
Additional Information
Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law:
The compensation range described below is the range of possible base pay compensation that the Company believes in good faith it will pay for this role at the time of thisposting based on the job grade for this position. Individual compensation paid within this range will depend on many factors including geographic location,and we may ultimately pay more or less than the posted range. This range may be modified in the future.
We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees.
This job is eligible to participate in our long-term incentive programs.
Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission,incentive, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole and absolute discretion unless anduntil paid and may be modified at the Company’s sole and absolute discretion, consistent with applicable law.
AbbVie is an equal opportunity employer and is committed to operating with integrity, driving innovation, transforming lives and serving our community. Equal Opportunity Employer/Veterans/Disabled.
US & Puerto Rico only - to learn more, visit https://www.abbvie.com/join-us/equal-employment-opportunity-employer.html
US & Puerto Rico applicants seeking a reasonable accommodation, click here to learn more:
https://www.abbvie.com/join-us/reasonable-accommodations.html