Associate Director, Epidemiological Statistical Programming FSP

Cytel•United States,

About The Position

The Associate Director, Epidemiological Statistical Programming is a senior technical leader in the Epidemiology programming function, providing functional guidance, technical expertise, and mentorship to statistical programmers while contributing directly to complex epidemiological projects. Working with a high degree of independence, this role translates project and scientific objectives into programming strategies, manages priorities and deliverables, and provides technical consultation to colleagues and cross-functional partners. The role leads and supports statistical programming for epidemiological and real-world evidence studies, ensuring analyses and data outputs are accurate, reproducible, consistent, and high quality. It may provide technical oversight of internal and external programming resources, including CRO partners, and promotes programming standards, efficient processes, and best practices. The Associate Director also develops team capabilities through mentoring, technical review, process improvement, automation, and support for appropriate allocation and execution of work. This is a sponsor-dedicated role, working fully embedded within a pharmaceutical client’s organization, with support from Cytel. The position collaborates with epidemiologists, statisticians, data scientists, and other partners to support evidence generation across multiple therapeutic areas.

Requirements

Bachelor’s degree or higher in Statistics, Biostatistics, Epidemiology, Computer Science, Data Science, Mathematics, or a related quantitative discipline.
At least 8 years of relevant statistical programming experience in the pharmaceutical, biotechnology, CRO, healthcare, or life sciences industry, supporting epidemiological, observational, real-world evidence, HEOR, or related research.
Experience with Optum and Truveta.
Advanced SAS and/or R programming expertise, including development, validation, and maintenance of complex analytical programs and reproducible workflows.
Strong experience with large and complex healthcare data, such as administrative claims, electronic health records, patient registries, or other real-world data.
Understanding of epidemiological study designs, statistical analysis methods, and programming applications in observational and real-world research.
Ability to provide technical leadership and guidance to statistical programmers, mentor colleagues, review programming approaches and deliverables, and resolve complex technical challenges.
Experience leading or coordinating programming activities across multiple projects, prioritizing deliverables, identifying risks and dependencies, and ensuring work meets quality standards and timelines.
Experience overseeing and reviewing programming deliverables.
Experience line managing a team.
Commitment to programming quality, reproducibility, documentation, and development and implementation of programming standards and best practices.
Ability to work independently, exercise sound technical judgment, and manage multiple priorities in a dynamic, cross-functional environment.
Excellent written and verbal communication skills and ability to explain complex technical concepts to technical and non-technical stakeholders.
Strong collaboration and leadership skills, including the ability to influence, mentor, and build relationships across multidisciplinary and geographically dispersed teams.

Nice To Haves

Master’s degree or higher in Statistics, Biostatistics, Epidemiology, Data Science, Computer Science, or another relevant quantitative discipline.
Experience programming across multiple epidemiological and real-world data sources and/or therapeutic areas.
Experience supporting regulatory-grade real-world evidence, regulatory submissions, health authority requests, or other evidence-generation activities.
Experience with additional programming languages, technologies, and analytical tools such as Python, SQL, Git, Unix/Linux, R Markdown/Quarto, or Shiny.
Experience developing reusable programming tools, packages, macros, automated workflows, or other solutions that improve efficiency, quality, and scalability.
Experience contributing to programming standards, SOPs, work instructions, technical guidance, or organizational best practices.
Experience with cloud-based analytics platforms and/or modern data environments.

Responsibilities

Provide technical and functional leadership to statistical programmers supporting epidemiological and real-world evidence studies, including mentoring, technical guidance, and promotion of consistent, high-quality programming practices.
Lead and contribute hands-on to programming for epidemiological studies across multiple therapeutic areas, translating study objectives, protocols, and statistical analysis plans into robust, reproducible analytical solutions.
Develop, validate, and maintain SAS and/or R programs for analysis datasets, statistical outputs, tables, figures, and other data products.
Partner with epidemiologists, statisticians, data scientists, and cross-functional stakeholders to determine programming approaches and ensure accurate, efficient implementation of analyses.
Provide technical consultation on complex programming, data, and analytical challenges, advising colleagues and stakeholders on appropriate solutions and best practices.
Oversee and review programming deliverables for accuracy, reproducibility, consistency, quality, and adherence to timelines and standards.
Support programming using real-world and observational data, potentially including administrative claims, electronic health records, registries, and other healthcare databases.
Develop analysis-ready datasets and programming specifications, including data transformations, derivation logic, quality-control procedures, and documentation.
Establish and enhance programming standards, reusable tools, macros, code libraries, documentation, and quality-control processes.
Identify and drive opportunities for automation, standardization, process improvement, and innovative approaches to improve efficiency, scalability, and quality.
Contribute to planning and prioritization across projects, identifying resource needs, technical risks, dependencies, and delivery challenges.
Support scientific deliverables such as regulatory and health authority requests, publications, abstracts, presentations, and evidence-generation activities supporting clinical development, medical affairs, and/or value and access objectives.
Ensure programming complies with applicable regulatory requirements, company policies, SOPs, data privacy requirements, and industry best practices.
Lead or contribute to SOPs, work instructions, programming conventions, and other documentation governing epidemiological statistical programming.
Foster collaboration across internal and external teams and develop programming talent through coaching, knowledge sharing, technical review, and mentorship.