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Cytel

Associate Director, Epidemiological Statistical Programming FSP

Canada

Full-time

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Job details

Job type: Full-time
Posting language: English
Posted: Aug 18, 2026

Original job description

Sponsor-dedicated

JOB DESCRIPTION

Working fully embedded within one of our pharmaceutical clients, with the support of Cytel right behind you, you'll be at the heart of our client's innovation. As a Principal Statistical Programmer you will be dedicated to one of our global pharmaceutical clients; a company that is driving the next generation of patient treatment, where individuals are empowered to work with autonomy and ownership. This is an exciting time to be a part of this new program.

Position Overview

The Associate Director, Epidemiological Statistical Programming serves as a senior technical leader within the Epidemiology programming function, providing functional guidance, technical expertise, and mentorship to statistical programmers while also contributing directly to complex epidemiological projects. Working with a high degree of independence, this individual translates project and scientific objectives into effective programming strategies, proactively manages priorities and deliverables, and provides expert technical consultation to team members and cross-functional partners.

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.

Responsibilities

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.

Qualifications

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.

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More about this job

Responsibilities

The Associate Director provides technical leadership and mentorship to statistical programmers while executing complex epidemiological and real-world evidence studies. They are responsible for developing reproducible analytical solutions and ensuring the quality and accuracy of data outputs across multiple therapeutic areas.

Requirements

Candidates must have a bachelor's degree in a quantitative field and at least 8 years of statistical programming experience in the pharmaceutical or life sciences industry. Proficiency in SAS or R and experience working with large healthcare data sources like EHR and claims are essential.

Skills

SAS
R
Epidemiological Statistical Programming
Real-World Evidence
HEOR
Technical Leadership
Data Analysis
Clinical Development
Mentorship
Project Management
Quality Control
Regulatory Submissions
Optum
Truveta
Electronic Health Records
Administrative Claims

Visa sponsorship

Not detected in the job text

Keywords

SAS
R
Epidemiology
Real-World Evidence
RWE
HEOR
Biostatistics
Optum
Truveta
Electronic Health Records
EHR
Administrative Claims
Data Science
Clinical Development
Medical Affairs
Regulatory Submissions
Python
SQL
Git
Unix/Linux
R Markdown
Quarto
Shiny
Cloud Analytics
SOPs
Pharmaceuticals
Biotechnology
CRO
Healthcare Data
Statistical Analysis Plans

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