The Associate Director is responsible for leading and supporting the implementation of statistical programming activities across epidemiological and real-world evidence studies, ensuring that analyses and data outputs are accurate, reproducible, consistent, and delivered to a high standard of quality. This role may provide technical oversight of internal and external programming resources, including CRO partners, and will establish and promote programming standards, efficient processes, and best practices across projects.
In addition to hands-on project responsibilities, the Associate Director will play an important role in developing programming capabilities within the team by mentoring colleagues, reviewing and advising on technical approaches, identifying opportunities for process improvement and automation, and helping ensure appropriate allocation and execution of programming work. The individual will collaborate closely with epidemiologists, statisticians, data scientists, and other cross-functional partners to support the generation of high-quality evidence across multiple therapeutic areas.
As an Associate Director, Epidemiological Statistical Programming, your responsibilities will include:
- Provide technical and functional leadership to statistical programmers supporting epidemiological and real-world evidence (RWE) studies, including mentoring team members, providing technical guidance, and promoting consistent, high-quality programming practices.
- Lead and contribute hands-on to statistical programming activities for epidemiological studies across multiple therapeutic areas, translating study objectives, protocols, and statistical analysis plans into robust and reproducible analytical solutions.
- Develop, validate, and maintain high-quality SAS and/or R programs to support the creation of analysis datasets, statistical outputs, tables, figures, and other data products required for epidemiological research and evidence generation.
- Partner closely with epidemiologists, statisticians, data scientists, and other cross-functional stakeholders to determine appropriate programming approaches and ensure analyses are implemented accurately and efficiently.
- Provide expert technical consultation on complex programming, data, and analytical challenges, identifying appropriate solutions and advising team members and project stakeholders on best practices.
- Oversee and review programming deliverables to ensure accuracy, reproducibility, consistency, quality, and adherence to agreed timelines and standards.
- Support programming activities using a variety of real-world and observational data sources, which may include administrative claims, electronic health records, registries, and other healthcare databases.
- Lead or contribute to the development of analysis-ready datasets and programming specifications, including data transformations, derivation logic, quality-control procedures, and documentation necessary to ensure transparent and reproducible analyses.
- Establish, enhance, and promote programming standards, reusable tools, macros, code libraries, documentation, and quality-control processes that improve efficiency and consistency across epidemiological projects.
- Drive continuous improvement and identify opportunities for automation, standardization, and innovative programming approaches that enhance the scalability and quality of epidemiological programming activities.
- Contribute to the planning and prioritization of programming activities across projects, proactively identifying resource needs, technical risks, dependencies, and potential challenges to successful delivery.
- Support scientific deliverables including regulatory and health authority requests, publications, abstracts, presentations, evidence-generation activities, and other analyses supporting clinical development, medical affairs, and/or value and access objectives.
- Ensure programming activities are conducted in accordance with applicable regulatory requirements, company policies, SOPs, data privacy requirements, and industry best practices.
- Lead or contribute to the development and maintenance of SOPs, work instructions, programming conventions, and other documentation governing epidemiological statistical programming activities.
- Foster strong collaboration across internal and external teams and contribute to the development of programming talent through coaching, knowledge sharing, technical review, and mentorship.
Here at Cytel, we want our employees to succeed, and we enable that success through consistent training, development, and support. To be successful in this position, you will have:
- Bachelor’s degree or higher in Statistics, Biostatistics, Epidemiology, Computer Science, Data Science, Mathematics, or a related quantitative discipline; advanced degree is a plus.
- 8+ years of relevant statistical programming experience within the pharmaceutical, biotechnology, CRO, healthcare, or life sciences industry, with demonstrated experience supporting epidemiological, observational, real-world evidence (RWE), HEOR, and/or related research.
- Experience with Optum and Truveta.
- Advanced programming expertise in SAS and/or R, with demonstrated ability to develop, validate, and maintain complex analytical programs and reproducible programming workflows.
- Strong experience working with large and complex healthcare data sources, such as administrative claims, electronic health records (EHR), patient registries, or other real-world data sources.
- Demonstrated understanding of epidemiological study designs, statistical analysis methods, and the application of programming techniques to observational and real-world research.
- Proven ability to provide technical leadership and guidance to statistical programmers, including mentoring colleagues, reviewing programming approaches and deliverables, and resolving complex technical challenges.
- Experience leading or coordinating programming activities across multiple projects, including prioritizing deliverables, identifying risks and dependencies, and ensuring work is completed to established quality standards and timelines.
- Experience overseeing and reviewing programming deliverables.
- Experience with line managing a team.
- Strong commitment to programming quality, reproducibility, documentation, and the development and implementation of programming standards and best practices.
- Ability to work independently, exercise sound technical judgment, and effectively manage multiple priorities in a dynamic, cross-functional environment.
- Excellent written and verbal communication skills, with the ability to communicate complex technical concepts effectively to both technical and non-technical stakeholders.
- Strong collaboration and leadership skills, with demonstrated ability to influence, mentor, and build effective working relationships across multidisciplinary and geographically dispersed teams.
Preferred Qualifications (Nice to Have)
- 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 RWE, 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, Shiny, or similar tools.
- Experience developing reusable programming tools, packages, macros, automated workflows, or other solutions that improve programming 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.
Skills Required
- Bachelor's degree or higher in Statistics, Biostatistics, Epidemiology, Computer Science, Data Science, Mathematics, or a related quantitative discipline
- 8+ years of relevant statistical programming experience in pharmaceutical, biotechnology, CRO, healthcare, or life sciences environments
- Experience supporting epidemiological, observational, real-world evidence, HEOR, or related research
- Experience with Optum and Truveta
- Advanced programming expertise in SAS and/or R
- Experience developing, validating, and maintaining complex analytical programs and reproducible workflows
- Experience working with large and complex healthcare data sources, including administrative claims, EHRs, patient registries, or other real-world data
- Understanding of epidemiological study designs, statistical analysis methods, and observational or real-world research programming
- Experience providing technical leadership, mentoring statistical programmers, reviewing programming approaches, and resolving complex technical challenges
- Experience leading or coordinating programming activities across multiple projects, including prioritization, risk identification, and dependency management
- Experience overseeing and reviewing programming deliverables
- Experience line managing a team
- Commitment to programming quality, reproducibility, documentation, standards, and best practices
- Ability to work independently, exercise technical judgment, and manage multiple priorities
- Excellent written and verbal communication skills
- Strong collaboration, leadership, mentoring, and stakeholder-influence skills
- Master's degree or higher in a relevant quantitative discipline
- Experience across multiple epidemiological or real-world data sources and therapeutic areas
- Experience supporting regulatory-grade RWE, regulatory submissions, health authority requests, or evidence-generation activities
- Experience with Python, SQL, Git, Unix/Linux, R Markdown, Quarto, Shiny, or similar tools
- Experience developing reusable tools, packages, macros, automated workflows, or scalable programming solutions
- Experience contributing to programming standards, SOPs, work instructions, technical guidance, or organizational best practices
- Experience with cloud-based analytics platforms or modern data environments
Cytel Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Cytel and has not been reviewed or approved by Cytel.
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Healthcare Strength — Health coverage is described as comprehensive, spanning medical, dental, vision, life and disability, with FSAs/HSAs also available. Plan quality is often characterized as good to excellent, which lifts the perceived value of the overall package.
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Retirement Support — A 401(k) with employer match is consistently part of the benefits package. The plan is also characterized as well managed, contributing to a sense of baseline retirement support.
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Fair & Transparent Compensation — Overall pay is characterized as decent-to-good and broadly competitive in parts of the business, with stronger alignment noted in senior technical tracks like biostatistics and programming. The total package is often framed as respectable rather than premium.
Cytel Insights
What We Do
Cytel enables decision-makers in the life sciences to unlock the full potential of their products. From navigating uncertainty to proving value, Cytel’s 30 years of global expertise in consulting, data-driven analytics, and industry-leading software helps biotech and pharmaceutical companies transform intelligence into confident decisions. We have an uncompromising commitment to scientific rigor and high standards of operational excellence, which are channeled through our locations in North America, Europe, the United Kingdom, and Asia. Together, we enable our clients to deliver the therapies that propel humanity forward. Cytel employs a range of data science tools from biostatistics to machine learning to help executives in the life-sciences to make confident decisions powered by data. We are probably best known for being leaders in the field of adaptive clinical trial design, a subset of trial design that uses interim looks to enhance the patient safety and commercial value of pharmaceutical products. We also have specialists in Bayesian statistics, real world evidence, artificial intelligence, health economics, and a number of other research fields to ensure that academic and scientific findings can have impact on industry quickly and seamlessly. www.cytel.com
