Principal Statistical Programmer FSP - RWD/EPI

Jobgether; Canada; Remote; CAD 120,000 - 170,000; Full time

Benefits offered by this job

Remote work

Impactful RWE research

Cross‑functional collaboration

Job summary

Jobgether is seeking a Principal Statistical Programmer FSP to advance real‑world evidence and epidemiology research in Canada. You will transform healthcare data into actionable insights and work with epidemiologists, statisticians, and stakeholders on observational studies.

The role emphasizes statistical programming, data management, and applied analytics using large RWD sources, with opportunities to contribute to regulatory documentation and clinical development decisions in a fully remote

Qualifications

• Master’s degree or PhD in Epidemiology, Biostatistics, Statistics, Bioinformatics, Economics, or a related quantitative discipline.
• At least 5 years of experience conducting real‑world evidence analytics within the pharmaceutical industry, a CRO, or an academic institution.
• Intermediate‑to‑expert proficiency in SQL is essential.
• Strong programming proficiency in SAS or R.
• Extensive experience analyzing real‑world data sources, particularly healthcare claims and electronic health records.
• Familiarity with major real‑world data platforms and sources such as Optum Clinformatics Datamart®, Market Clarity, Truveta, and UK Biobank.
• Experience working with clinical trial or registry data is an advantage.
• Strong understanding of relational databases, healthcare claims structures, and ancillary file layouts.
• Applied statistical expertise, including regression methods (OLS, longitudinal, logistic, Cox, GLM, GEE).
• Experience with survival analysis techniques (Kaplan–Meier, cumulative incidence, AFT).
• Knowledge of propensity weighting and other methods used in observational research.
• Excellent project management and organizational skills.
• Confidence working with internal and external stakeholders.
• Strong written and verbal communication skills.

Responsibilities

• Support epidemiology teams by preparing real‑world data and advising on analytical strategies.
• Assist in developing study protocols and statistical analysis plans using large real‑world data sources.
• Coordinate with data vendors to obtain relevant data extracts in line with study protocols.
• Build and maintain analytical databases to support statistical analyses.
• Program and conduct statistical analyses under supervision of epidemiologists and statisticians.
• Perform analyses per study protocols using appropriate statistical methods.
• Generate tables, figures, visualizations, and reports for investigators and clients.
• Support standardization, visualization, and reporting of observational data.
• Contribute to Medical Affairs observational studies and Global Patient Safety analyses.
• Assist with study reports and present findings internally and to clients.
• Manage relationships with stakeholders and ensure timely delivery of high‑quality work.
• Troubleshoot technical challenges and provide analytical support.
• Potentially take on supervisory responsibilities as needed.

Skills

SQL

SAS/R

Epidemiology

Data management

Real‑world data

Study protocols

Results communication

Project management

Clinical research

Survival analysis

Cox models

Education

Master’s or PhD in Epidemiology/Biostatistics

Tools

SAS

R

SQL

Job description

Our partner is looking for a Principal Statistical Programmer FSP – RWD/EPI based in Canada.

This is an opportunity to contribute to real‑world evidence (RWE) and epidemiology research by transforming complex healthcare data into meaningful analytical insights. You will work closely with epidemiologists, statisticians, and cross‑functional stakeholders to support observational studies and evidence generation. The role combines advanced statistical programming, data management, and applied analytical methods using large real‑world data sources. Your work will inform research strategies, regulatory and safety documentation, and clinical development decisions. You will collaborate with internal teams and external partners while managing multiple projects and deliverables. This is a full‑time, remote position suited to an experienced statistical programming professional with strong technical and communication skills.

Accountabilities

• Support epidemiology teams by preparing real‑world data, advising on analytical strategies, and contributing to epidemiological research activities.

• Assist in developing study protocols and statistical analysis plans using large real‑world data sources, including healthcare claims and electronic health records (EHR).

• Coordinate with data vendors to obtain relevant data extracts in accordance with approved study protocols.

• Build and maintain analytical databases from source data extracts to support statistical analyses.

• Program and conduct statistical analyses under the direction of epidemiologists and statisticians, including data coding, algorithm development, dataset linkage, and application of statistical methods.

• Perform analyses according to study protocols and analysis plans, using appropriate statistical programming tools and techniques.

• Generate tables, figures, visualizations, and reports to communicate observational research findings to investigators, clients, and internal stakeholders.

• Support the standardization, visualization, and reporting of observational data through innovative programming approaches.

• Contribute to Medical Affairs observational studies, Global Patient Safety and Risk Management analyses, and Clinical Development activities, including background‑rate assessments and patient population or protocol feasibility evaluations.

• Assist with study reports and other research deliverables, and present findings internally and to clients.

• Manage relationships with internal and external stakeholders, prioritize competing project requirements, and ensure timely delivery of high‑quality work.

• Troubleshoot technical challenges and provide reliable programming and analytical support.

• Potentially take on supervisory responsibilities as the role and team needs evolve.

Requirements

• Master’s degree or PhD in Epidemiology, Biostatistics, Statistics, Bioinformatics, Economics, or a related quantitative discipline.

• At least 5 years of experience conducting real‑world evidence analytics within the pharmaceutical industry, a contract research organization (CRO), or an academic institution.

• Intermediate‑to‑expert proficiency in SQL is essential.

• Strong programming proficiency in SAS or R.

• Extensive experience analyzing real‑world data sources, particularly healthcare claims and electronic health records.

• Familiarity with major real‑world data platforms and sources such as Optum Clinformatics Datamart®, Market Clarity, Truveta, and UK Biobank.

• Experience working with clinical trial or registry data is an advantage.

• Strong understanding of relational databases, healthcare claims structures, and ancillary file layouts.

• Applied statistical expertise, including regression methods such as ordinary least squares (OLS), longitudinal, logistic, Cox, generalized linear models (GLM), and generalized estimating equations (GEE).

• Experience with survival analysis techniques, including Kaplan–Meier estimates, cumulative incidence, and accelerated failure time models.

• Knowledge of propensity weighting and other methods used in observational research.

• Excellent project management and organizational skills, with the ability to prioritize multiple assignments and meet deadlines.

• Confidence working with internal and external stakeholders, including data vendors, investigators, and clients.

• Strong written and verbal communication skills, with the ability to summarize complex analytical findings and present key evidence clearly.

Benefits

• Full‑time, remote work arrangement.

• Opportunity to contribute to impactful real‑world evidence and epidemiology research.

• Collaboration with multidisciplinary experts and stakeholders across research and development.

• Exposure to complex healthcare datasets, advanced statistical methods, and diverse research projects.