Lead the definition, implementation and governance of Pierre Fabre's Clinical Data Standards Strategy, including the CDISC-based sponsor standards library.
Responsibilities
Lead the definition, implementation and governance of Pierre Fabre's Clinical Data Standards Strategy.
Own and evolve the Pierre Fabre Sponsor Standards Library built on top of CDISC standards.
Establish standards governance processes, lifecycle management, version control and change management practices.
Lead the development, maintenance and governance of standards covering eCRF libraries, SDTM, ADaM, edit checks, controlled terminology and study metadata.
Ensure Pierre Fabre standards remain aligned with evolving regulatory expectations and industry best practices.
Requirements
Master's Degree or PhD in life sciences, data management, statistics, programming or a related field
Provide hands‑on statistical programming support for clinical studies, developing and validating analysis datasets, tables, listings, figures, and graphs for regulatory submissions and internal presentations.
Compensation
Bill Rate is *** On Site or Remote Provide hands‐on statistical programming support for clinical studies, including development and validation of analysis datasets and statistical outputs, in accordance with regulatory and company standards.
Responsibilities
Develop complex analysis datasets, specifications, and summary outputs
Create, modify, and maintain SAS programs
Perform independent program review and validation
Support ad hoc and planned analyses
Partner with Clinical Data Management and Biostatistics
Requirements
Bachelor’s degree in Statistics, Mathematics, Computer Science, or a related field
Master’s degree (or equivalent) in a related field
Nice to have: R
Nice to have: Python
Nice to have: Experience with regulatory submissions
This role drives the statistical strategy and execution behind Denali's core clinical development programs, translating complex data into insights that inform therapeutic decisions for neurodegenerative disease programs.
Compensation
Salary Range: $155,000.00 to $202,000.00
Responsibilities
Leads development of key clinical study deliverables, including statistical analysis plans, protocol statistical sections, and clinical study reports.
Ensures statistical integrity and accuracy of analysis and reporting deliverables, meeting pre-specified requirements, internal SOPs, and external regulatory standards.
Conducts hands-on exploratory analyses, sample size estimation, and modeling/simulation; builds tools to extract insights from data.
Interprets and presents data and statistical considerations to internal project teams and senior management.
Oversees Biostatistics vendors and contract research organizations, providing quality oversight of in-house and external statistical deliverables.
Requirements
PhD in Statistics, Biostatistics, or a related discipline
Lead and oversee all clinical data management activities across multiple therapeutic areas, ensuring compliance with regulatory standards and driving process improvements.
Compensation
Salary Range: $212,000.00 to $276,000.00 . Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience.
Responsibilities
Provide leadership and oversight for the execution of clinical data management activities across multiple therapeutic areas and molecules.
Lead CDM activities at the project or study level, as needed.
Manage a team of Managers and Clinical Data Associates, ensuring effective support for complex data management needs.
Direct and guide team through DM lifecycle associated with P1-P3 studies, including pivotal, blinded, and randomized trials.
Lead direct report(s) through annual goal setting, growth planning, adherence to company policies, maintain training compliance and provide ongoing feedback on growth, development and areas of improvement.
Requirements
BA/BS or higher in math, science, or health-related field
Nice to have: prior experience supporting regulatory submissions
Nice to have: preparing for and supporting regulatory inspections and audits
This role will shape and drive the enterprise-aligned AI strategy for Immunology R&D and translate that strategy into an executable, value-focused portfolio of AI capabilities, data products, and AI solutions. It is a senior executive leadership role at the intersection of Immunology discovery & clinical science, data, AI, product strategy, and organizational execution.
Lead biostatistician overseeing complex clinical trial studies, managing statistical strategy, design, analysis, and regulatory submissions.
Responsibilities
Serve as lead statistician on complex, key client studies
Act as point-of-contact ensuring cohesive communication with sponsors and internal teams
Lead project-level statistical strategy from protocol/SAP planning through reporting
Develop sample size estimation, modeling approaches, adaptive or Bayesian frameworks, and innovative trial designs
Provide senior oversight for statistical deliverables including SAPs, randomization specifications, and statistical contributions to CSRs, publications, and regulatory documents
Requirements
Advanced degree (MS or PhD) in statistics or closely related field
Define and maintain the Immunology AI strategy, translating therapeutic-area priorities and pipeline needs into a clear multi-year roadmap of AI-enabled capabilities, data products, and solutions.
Lead strategic portfolio planning for Immunology AI, including opportunity identification, value framing, prioritization, sequencing, investment choices, dependencies, and resource alignment.
Create an integrated execution model across Immunology and enabling functions, with clear decision rights, accountable owners, milestones, risks, and measures of value.
Partner with Immunology scientific and development leaders to identify high-impact solutions across discovery, translational research, clinical development, biomarkers, evidence generation, and portfolio decision-making.
Provide technical leadership and informed challenges on AI solution design, data readiness, model suitability, validation, scalability, interoperability, and responsible use.
Requirements
Advanced degree (PhD, MD, PharmD, MS, or equivalent experience) in computer science, AI/ML, engineering, biomedical sciences, computational biology, applied mathematics, data science, or a related scientific discipline
StatisticianNewRoche · Shanghai, China