Senior Manager, Statistical Programming

Location: New York

Job Summary The Senior Manager, Statistical Programming is responsible for leading and participating in the development and validation of datasets, tables, figures, and listings (TFLs) that support the analysis and reporting of clinical trials and for providing expertise for statistical programming activities. This role will be expected to develop collaborative relationships and work effectively within the Statistical Programming team, with cross-functional teams, and external vendors.

Job Description Create SAS programs and AI-assisted programming solutions to perform end-to-end statistical programming activities including SDTM, ADaM, and content for TFLsPerform programming validation and quality review to ensure the accuracy, reproducibility, and integrity of analysis datasets, programming outputs, and AI-generated deliverables

Provide programming support for project teams, including development of programming strategies, standards, specifications, programmed analyses, and AI-enabled programming approaches

Lead and/or support submission preparations, deliverables, and regulatory responses

Review key planning documents (e.g., statistical analysis plan, data presentation plan, data review plan) to ensure alignment with development team objectives and clarity and completeness of programming assumptions and requirements; assess impact on programming activities

Develop or review validation plans for programming deliverables to ensure quality and consistency of outputs

Interact with vendors regarding project standards, programming conventions, programming specifications, file transfers, and AI-enabled programming practices, as applicable

Provide leadership in ensuring quality of deliverables by consistently applying standards and complying with regulatory requirements, guidance, and corporate and departmental SOPs and working practices.

Identify opportunities for increased efficiency, consistency, automation, and quality within Statistical Programming and interactions with vendors through innovative programming approaches and appropriate use of AI-enabled technologies

Independently lead and perform programming assignments with minimal supervision

Lead and/or participate in process improvement, standards, automation, and AI adoption initiatives that enhance productivity, quality, scalability, and consistency across Statistical Programming Supervise contract workers and provide guidance on programming standards, quality expectations, and effective use of AI-enabled programming tools and workflows

Evaluate, implement, and champion emerging AI-enabled programming capabilities to streamline workflows, accelerate deliverable development, and drive continuous improvement while maintaining appropriate quality, traceability, and regulatory controls

Qualifications/ Required Knowledge/

Experience and Skills:

Demonstrate proficiency in using SAS, R (preferrable), and AI-enabled programming tools to produce derived analysis datasets and TFLsKnowledge of CDISC standards, relational database structures, and industry data standards.

Experience using software tools and applications (e.g., MS Office, XML, Pinnacle 21) and the ability to effectively adopt and apply emerging AI-enabled technologies

Ability to provide outputs that meet submission requirements, including ADaM datasets, define.xml files, reviewer guides, and other regulatory deliverables

Strong knowledge of regulatory, industry, and technology standards and requirements, including the appropriate use of AI-enabled tools in regulated environments

Good knowledge of the drug development process, clinical trials, medical terminology, statistical analysis plans, and protocol designs

Ability to work effectively in a team environment with clinical team members, vendors, and cross-functional stakeholders

Demonstrated ability to identify opportunities to improve productivity, quality, consistency, and automation through innovative programming approaches and AI-enabled solutions

Ability to critically evaluate, validate, and oversee AI-generated outputs to ensure accuracy, reproducibility, traceability, and compliance with established standards and procedures

Ability to support and influence the adoption of new technologies, standards, and AI-enabled programming practices across project teams

Experience supporting rare disease therapeutic areas and/or PK/PD analyses, preferred but not required

Master's degree in Statistics, Biostatistics, Mathematics, Computer Science, Life Sciences, or equivalent preferred,…