Principal Programmer - RWD/EPI

Accountabilities:: Support epidemiology teams by preparing and processing real-world data, advising on analytical strategies, and contributing to a wide range of epidemiological research activities. Contribute to the development of study protocols and statistical analysis plans using large real-world data sources, including healthcare claims databases and electronic health records (EHR). Collaborate with external data vendors to identify, request, and obtain relevant data extracts for research studies, ensuring alignment with established study protocols and analytical requirements. Design, develop, and maintain analytical databases from raw data extracts to facilitate accurate and efficient statistical analyses. Perform statistical programming and analyses under the guidance of epidemiologists and statisticians, including data coding, algorithm development, dataset linkage, and implementation of appropriate statistical methods. Conduct analyses in accordance with approved study protocols and statistical analysis plans, ensuring data accuracy, consistency, and scientific rigor. Develop and implement innovative approaches to data standardization, visualization, and reporting to improve the interpretation and presentation of observational research findings. Produce high-quality statistical tables, figures, and analytical outputs for discussions with investigators, clients, and other research stakeholders. Support Medical Affairs initiatives, including observational studies leveraging real-world data to generate meaningful clinical and scientific insights. Contribute to Global Patient Safety and Risk Management activities, including analyses designed to establish background rates and support the preparation of regulatory and safety documentation. Support Clinical Development initiatives through analyses of patient populations, feasibility assessments, and protocol development activities. Prepare study reports, technical documentation, presentations, and other project deliverables, ensuring that results are communicated clearly and effectively. Present analytical findings and key insights internally and directly to clients, translating complex statistical information into understandable recommendations. Build and maintain effective relationships with internal teams, epidemiologists, external stakeholders, and data providers to ensure successful project execution. Manage multiple projects and competing priorities while maintaining high standards of accuracy, efficiency, and timely delivery. Troubleshoot technical challenges and provide expert programming solutions to support research objectives and project outcomes. Potentially take on future supervisory responsibilities, contributing to team development, technical guidance, and knowledge sharing. Requirements: Master's degree or PhD in Epidemiology, Biostatistics, Statistics, Bioinformatics, Economics, or another closely related quantitative discipline. At least five years of professional experience conducting real-world evidence (RWE) analytics within the pharmaceutical industry, a Contract Research Organization (CRO), or an academic research institution. Intermediate to advanced proficiency in SQL, which is essential for managing, querying, and analyzing large healthcare datasets. Strong programming proficiency in SAS or R, with the ability to develop and execute complex statistical programming workflows. Extensive experience analyzing real-world evidence data sources, particularly Optum (Clinformatics Datamart® and Market Clarity), Truveta, and UK Biobank. Familiarity with clinical trial data and/or patient registry data is considered an asset. Strong understanding of relational databases, healthcare data structures, and the organization and interpretation of medical claims and ancillary file layouts. Demonstrated expertise in applied statistical methodologies, including: Regression analysis, such as ordinary least squares (OLS), longitudinal regression, logistic regression, Cox regression, and generalized linear models (GLM/GEE). Survival analysis techniques, including Kaplan-Meier estimation, cumulative incidence, and accelerated failure time models. Propensity score methods and propensity weighting approaches. Ability to develop analytical datasets, implement statistical algorithms, link multiple data sources, and ensure data integrity throughout the research process. Strong understanding of epidemiological research methods and the application of real-world data in observational studies and healthcare research. Excellent project management and organizational skills, with the ability to prioritize multiple assignments, manage competing deadlines, and deliver high-quality results on schedule. Strong interpersonal and stakeholder management skills, with confidence in collaborating with internal teams, external partners, data vendors, and clients. Excellent written and verbal communication skills, including the ability to summarize complex analytical findings, present scientific evidence, and communicate key considerations effectively. Strong analytical thinking, technical problem-solving abilities, attention to detail, and a proactive approach to overcoming research and programming challenges. Ability to work independently while contributing effectively to multidisciplinary teams and supporting shared project objectives. Benefits: Competitive compensation package based on qualifications and professional experience. Permanent, full-time employment opportunity. Fully remote working arrangement within Canada. Opportunity to work on innovative real-world evidence and epidemiological research projects. Exposure to large-scale healthcare databases and advanced statistical programming methodologies. Collaboration with experienced epidemiologists, biostatisticians, statisticians, and pharmaceutical industry professionals. Opportunity to contribute to research supporting Medical Affairs, Clinical Development, Global Patient Safety, and regulatory decision-making. Exposure to diverse projects involving observational studies, healthcare analytics, and real-world data methodologies. Opportunities for professional development and continuous learning in an evolving scientific and technological environment. Potential to take on future supervisory responsibilities and contribute to team leadership and development. Opportunity to make a meaningful contribution to evidence generation and research initiatives that support improved healthcare decisions and patient outcomes.