Clinical Content Associate Director – Clinical AI Scientific Evidence and Publications (UpToDate®)

LOCATION: U.S. locations – remote/hybrid (8 days a month in the office). For physicians - Candidates within commuting distance of a Wolters Kluwer office will be considered for hybrid employment (within 50 miles of an office). Candidates not within commuting distances will be considered for remote employment. For other clinicians, you will be hybrid to office locations. Please see eligible locations on the posting.

OVERVIEW

The Scientific Evidence and Publications Associate Director for UpToDate ® will support the development of the scientific evidence base and external credibility of our clinical AI platform. This individual will lead assigned publication initiatives, contribute to evidence development, and translate analytical findings into clear, credible scientific communications.

The role sits at the intersection of clinical research, data analysis, scientific communication, and artificial intelligence. The Associate Director will work closely with clinicians, biostatisticians, data scientists, engineers, product leaders, medical editors, academic collaborators, and professional societies to produce rigorous and useful scientific outputs.

The successful candidate will bring strong knowledge of clinical research and clinical trial methodology, excellent scientific writing skills, and the ability to interpret data and communicate findings clearly without losing scientific rigor. This is a hands-on role requiring independent judgment within defined objectives, leadership of complex scientific projects, and collaboration to apply and advance credible standards for clinical AI.

RESPONSIBILITIES

Scientific Publications and Communications

• •Contribute to and execute an integrated publication plan for the clinical AI platform, aligned with scientific and business priorities established with leadership.
• •Lead or coordinate the development of assigned peer-reviewed manuscripts, abstracts, posters, presentations, white papers, evidence summaries, protocols, and scientific reports.
• •Identify and recommend high-value publication opportunities arising from platform development, validation, monitoring, and real-world use.
• •Translate complex clinical, statistical, and technical findings into clear and compelling scientific narratives.
• •Develop effective tables, figures, data visualizations, and executive-level summaries.
• •Ensure consistency and accuracy in scientific claims, terminology, methods, and interpretation across assigned publications and communications.
• •Manage publication timelines, authorship plans, reviews, submissions, and collaboration across multiple concurrent projects; resolve project-level issues and seek leadership alignment when priorities or scope change.

Evidence Generation and Data Interpretation

• •Partner with clinical, statistical, research, and technical teams to design and execute studies evaluating the performance, safety, reliability, and clinical relevance of AI-enabled clinical decision support.
• •Contribute to research protocols, analysis plans, validation studies, comparative evaluations, observational studies, and prospective or retrospective clinical research.
• •Recommend appropriate outcomes, populations, comparators, evaluation criteria, subgroup analyses, and potential failure modes for assigned studies.
• •Review and interpret quantitative analyses generated by biostatisticians, data scientists, clinical evaluators, and external research partners.
• •Identify issues involving bias, confounding, missing data, generalizability, statistical uncertainty, or unsupported inference, and work with relevant experts to address them.
• •Assess whether available evidence supports proposed scientific, clinical, or product claims, and recommend appropriate qualifications or additional supporting work.
• •Identify evidence gaps and recommend additional analyses, studies, or collaborations to inform evidence-development priorities.

Clinical AI Evaluation

• •Develop and apply a strong understanding of the platform’s clinical content, evidence sources, reasoning methods, validation framework, governance, and monitoring processes.
• •Contribute to the development and application of methods for evaluating clinical AI, including clinical appropriateness, evidence alignment, reasoning quality, completeness, safety, usability, and potential for harm.
• •Distinguish among model performance, system performance, content quality, clinical reasoning quality, and real-world impact when interpreting and communicating findings.
• •Monitor developments in generative AI, clinical decision support, evaluation science, responsible AI, and relevant regulatory and professional standards; assess implications for assigned work.
• •Recommend opportunities to strengthen evaluation methods, benchmarks, and scientific collaborations, and contribute to approved initiatives.

External Collaboration and Scientific Quality

• •Develop and maintain relationships with academic investigators, clinical experts, professional societies, research institutions, and other external collaborators in support of agreed scientific priorities.
• •Coordinate or contribute to joint research projects, validation studies, advisory boards, consensus panels, conference presentations, and co-authored publications.
• •Represent assigned scientific work in meetings and discussions with external experts.
• •Apply rigorous standards for scientific review, data verification, authorship, disclosure, claim substantiation, and publication quality.
• •Partner with legal, regulatory, compliance, clinical, and product stakeholders to ensure external claims are accurate, appropriately supported, and clearly qualified.
• •Exercise independent scientific judgment within established objectives and review processes; seek leadership alignment on issues affecting broader strategy, organizational commitments, or scientific reputation.

QUALIFICATIONS

Education

Advanced degree in medicine, public health, epidemiology, biostatistics, health services research, biomedical informatics, outcomes research, or a related field. Relevant degrees may include MD, PhD, DrPH, MPH, MS, or an equivalent advanced degree.

Experience

• •Typically requires 8 or more years of relevant experience in clinical research, clinical trials, evidence generation, scientific publications, medical communications, or a related scientific discipline.
• •Demonstrated experience independently leading complex scientific or publication projects within defined objectives.
• •Experience authoring or leading peer-reviewed manuscripts, scientific reports, abstracts, presentations, or comparable scientific deliverables.
• •Strong understanding of clinical trial design, observational research, validation studies, statistical analysis, and interpretation of clinical data.
• •Experience working with quantitative datasets and collaborating with biostatisticians, data scientists, epidemiologists, or clinical researchers.
• •Experience translating complex scientific and analytical findings into clear written and visual communications.
• •Familiarity with artificial intelligence, machine learning, generative AI, clinical decision support, biomedical informatics, or digital health.
• •Experience working across clinical, scientific, technical, and business functions in a matrixed environment.

Preferred Qualifications

• •Experience evaluating AI-enabled clinical tools, clinical decision-support systems, diagnostic technologies, or digital health interventions.
• •Knowledge of evidence-based medicine, systematic review, clinical guidelines, or clinical content development.
• •Familiarity with AI evaluation methods, including benchmark design, expert review, inter-rater reliability, bias assessment, model validation, and post-deployment monitoring.
• •Experience with real-world evidence, pragmatic studies, comparative effectiveness research, or prospective clinical studies.
• •Experience collaborating with academic investigators, professional societies, clinical