Associate Director, Clinical Data Integration, AI Programming

This is a fully remote position, open to applicants in United States.

📋 Description

• Design, construct, and maintain automated clinical data ingestion pipelines featuring scheduling, versioning, audit trails, processing logs, and failure alerts.

• Take ownership of a standardized clinical data model and metadata-driven mapping specifications across studies and compounds.

• Develop automated workflows for data quality, congruency, reconciliation, exception routing, risk-based monitoring, and centralized data surveillance.

• Create controlled APIs and governed components for standardized clinical data access.

• Design, develop, validate, deploy, and maintain interactive R/Shiny and Python dashboards for clinical data review and monitoring of study health.

• Generate patient profiles, data review listings, edit check outputs, coding review reports, and medical review applications.

• Create reusable R and Python packages, modules, visualization components, dashboard templates, metric definitions, and navigation patterns.

• Automate communications for study teams with scheduled summaries of key metrics.

• Collaborate with Data Management, Clinical Operations, Clinical Development, Safety, Biostatistics, and Statistical Programming to translate review needs into dashboard functionalities and promote adoption.

• Operationalize Posit Workbench, Posit Connect, Package Manager, controlled package environments, application publishing, access management, and governed deployment.

• Establish development standards for R/Python, including code reviews, automated testing, error handling, logging, dependency management, Git version control, and CI/CD practices.

• Manage the lifecycle of pipelines, dashboards, and reusable components from requirements through validation, release, monitoring, enhancement, and retirement.

• Implement validation, documentation, quality, traceability, and change-control standards; act as a subject matter expert in support of audits and inspections.

• Evaluate and implement AI and generative AI capabilities for clinical data transformation, quality review, summarization, standards search, code assistance, and documentation.

• Integrate approved LLM and retrieval-augmented generation capabilities with appropriate governance.

• Apply human-in-the-loop reviews, acceptance criteria, traceability, and validation to AI-assisted outputs.

• Execute the clinical data integration, dashboard, and automation roadmap across assigned compounds, prioritizing backlog work.

• Lead technical and process improvement initiatives, recommending sourcing approaches and tools.

• Provide technical oversight of FSP, CRO, vendor, and consultant resources while reviewing their deliverables.

• Gather requirements, resolve issues, drive tool adoption, and offer training, mentoring, and technical guidance.

• Stay informed about developments in R, Python, Posit, clinical data engineering, and AI applications in drug development; recommend relevant advancements.

⛳️ Requirements

• Bachelor’s degree in statistics, biostatistics, computer science, data science, biomedical informatics, or a related science field; equivalent combinations of relevant education and experience may be considered.

• Aiming for 10 years of progressively responsible experience in statistical programming, clinical programming, clinical data engineering, or clinical analytics; proven experience in delivering technical solutions across multiple studies is essential.

• Advanced hands-on experience with R programming, including Shiny, tidyverse, data.table, R Markdown/Quarto, package development, modular application design, and reproducible workflows.

• Strong hands-on proficiency in Python for data ingestion, transformation, automation, analytics, and application development.

• Solid SQL skills and experience in building and consuming REST APIs.

• Demonstrated experience in developing and deploying interactive clinical dashboards, patient profiles, data review tools, or study monitoring applications for study teams.

• Proven experience in designing automated processes for ingestion, transformation, mapping, validation, and refreshing structured and semi-structured clinical data.

• Experience in standardizing and integrating EDC, laboratory, eCOA, safety, IRT, and operational data across multiple studies or programs.

• Familiarity with Posit/RStudio Workbench, Posit Connect, and Posit Package Manager, or comparable enterprise R and Python environments.

• Experience with Git version control, automated testing, CI/CD, logging, monitoring, and controlled software deployment.

• Strong understanding of clinical trial data and CDISC standards, including SDTM, ADaM, metadata-driven programming, and integrated data structures.

• Working knowledge of SAS and the ability to integrate established SAS workflows with modern R and Python solutions.

• Practical understanding of GenAI, LLMs, RAG, and AI-assisted programming in regulated environments, including limitations and validation implications.

• Comprehensive knowledge of GCP, ICH, 21 CFR part 11, data privacy, access control, audit trails, and validation expectations for clinical data systems.

• Excellent written and verbal communication skills.

• Ability to manage competing priorities and deadlines across multiple initiatives.

• Willingness and ability to travel domestically and internationally as needed.

• Capability to work independently from remote locations and travel independently overnight or work after hours as required.

🏝️ Benefits

• Competitive base salary, bonus, and new hire and ongoing equity packages.

• Medical, dental, and vision insurance coverage.

• Employer-paid life, disability, business travel, and EAP coverage.

• 401(k) Plan with a fully vested company match of 1:1 up to 5%.

• Employee Stock Purchase Plan with a 2-year purchase price lock-in.

• 15+ vacation days.

• 13 - 15 paid holidays, including office closure between December 24th and January 1st.

• 10 days of paid sick leave.

• Paid parental leave benefit.

• Tuition assistance.