Clinical Director I, Data and AI Convergence

Purpose:
Director, Clinical Data and AI Convergence: physician leader in AbbVie’s R&D Convergence Core Team, identifying/executing opportunities where data convergence, analytics, and AI transform clinical and translational decision-making and end-to-end workflows.

Responsibilities:
- Principal clinical integration authority for Convergence initiatives; ensure clinical relevance, scientific rigor, operational feasibility, and regulatory compliance.
- Assess existing workflows, identify systemic gaps, and architect AI-enabled analytical processes embedded across R&D (early to late-stage).
- Ensure workflow innovations create measurable pipeline value and enable enterprise-wide adoption.
- Primary clinical voice within the Convergence Data and AI team; translate therapeutic/functional priorities into scalable solutions.
- Partner across R&D to address workflow inefficiencies, bottlenecks, and decision gaps.
- Lead development of enterprise workflows integrating diverse data into unified, analytics-ready frameworks; ensure interoperability, user-centric design, and alignment with governance/decision forums/change management.
- Oversee clinical validation of AI outputs for patient selection, endpoint strategies, trial optimization, safety surveillance, and benefit–risk assessment.
- Co-create with clinicians, data scientists, biostatisticians, operations, and regulatory partners; drive adoption via training and demonstrations; disseminate best practices.

Qualifications (Clinical Director I):
- MD; 8–10 years in pharma/biotech clinical development or translational medicine; substantial experience transforming data-enabled workflows.
- Deep clinical development lifecycle knowledge (trial design/execution, regulatory submission, post-approval).
- Proven enterprise workflow transformation leadership integrating AI/advanced analytics/digital into regulated clinical operations.
- Strong therapeutic area variability/patient population/endpoint development/safety signal interpretation.
- Ability to translate clinical, technical, and operational perspectives; influence in matrixed organizations.

Preferred:
- Board certification; recent/ongoing clinical practice.
- Translational medicine/biomarker/precision medicine; ML/predictive modeling/statistics knowledge.
- Knowledge of CDISC and interoperability; change management in clinical orgs.
- Cloud platforms, big data architectures, enterprise data integration.

Technical Expertise:
- Advanced ML/AI (deep learning, neural nets, ensembles, transfer learning, generative AI).
- ML/AI frameworks (TensorFlow, PyTorch, Scikit-learn, Hugging Face).
- Python/R; software engineering, production code, version control, CI/CD, testing.
- MLOps/Ml lifecycle, orchestration (Airflow, Kubeflow, MLflow), deployment architectures.
- Cloud (AWS/Azure) and distributed computing; data architecture and integration.

Benefits (as stated):
- Paid time off (vacation/holidays/sick), medical/dental/vision insurance, 401(k) eligibility; short-term incentive program eligibility.