About the Role:
Responsible to execute on strategy to scale and accelerate biometrics deliverables by leveraging existing standards and processes to implement automation-centric, AI-enabled workflows that result in regulatory compliant data collection, analysis, and reporting. This role works closely with project leads in Data Management, Statistical Programming and Biostatistics to operationalize existing data and analysis requirements into automation-centric, AI-enabled workflows in a regulatory compliant framework deeply rooted in reusable metadata, lifecycle governance, content reuse and responsible-AI controls. This role will identify opportunities and partner with leadership to prioritize and design tools that facilitate seamless integration among Data Management, Statistical Programming and Biostatistics to scale and support a growing portfolio and ensure regulatory compliance and inspection readiness. Your Contributions (include, but are not limited to):Implement and champion continuous improvement of foundational standards that enable automation and consistent execution across studies (e.g., standards rulesets, mappings, reusable templates, workflow checklists, and controlled specifications) Drive standards implementation and operationalization aligned to CDISC expectations, including strong a linkage between CDASH-compliant data collection and downstream CDISC-compliant data and subsequent Neurocrine standard analysis/reporting Support design and quality of submission-critical outputs, including the Define-XML package, ensuring traceability, consistency and an inspection-readiness mindset Build and deploy low/no-code automations that improve: standards adherence and consistency, handoff quality between Data Management, Statistical Programming and Biostatistics, repeatability of analysis and reporting workflows, inspection readiness through controlled outputs and documentation Enable governed AI use within Biometrics (creating and implementing use cases, access restrictions, peer review, and automated checks) Define inspection-ready evidence for automated/AI-assisted outputs Provide training and technical support to end users for effective adoption and utilization of AI and automation solutions Shape, with buy-in and endorsement from ADS Leaders, the ADS technology strategy by guiding the adoption of innovative technologies and encouraging a culture of creativity and continuous improvement Drive innovation within biometrics by identifying and implementing new tools, technologies, and methodologies to enhance efficiency and effectiveness, while fostering collaboration with peers across relevant functional areas Other duties as assigned
Requirements:- BS/BA degree AND 10+ years of relevant biotech/pharma/CRO clinical development experience OR Master's degree AND 8+ years of related biotech/pharma/CRO clinical development experience OR PhD AND 5+ years of related biotech/pharma/CRO clinical development experience
- Considered an expert within the company and may have external presence in area of expertise
- Applies in-depth knowledge of own function, business / commercial / scientific expertise to solve critical issues successfully and innovatively
- Ability to work as part of and lead multiple teams
- Sees broader picture and longer-term impact on division/company
- Excellent leadership, coaching and development skills
- Strong negotiation and influencing skillsExcellent communication, problem-solving, analytical thinking skillsExcellent computer skillsExcellent organizational and time management skills with the ability to work independently and in a team environment to meet established deadlines
- Deep knowledge of CDASH and CDISC industry standards (e.g., SDTM, ADaM, Define.xml) and the increasingly complex regulatory requirements for delivering regulatory quality data
- Experience leveraging standards to create processes that facilitate automation and AI-driven solutions to optimize Analytic and Data Sciences deliverables
- Advanced SAS or R proficiency; +Python and SQL strongly preferred
- Experience with Medidata Rave EDC build and content reuse (CRF standards, edit checks, libraries) and downstream readiness
- Deep knowledge of GxP expectations, data integrity, audit trails, and partnering with IT/Quality on validation
