Statistical Programmer I

Everest Clinical Research (“Everest”) is a full-service contract research organization (CRO) providing a broad range of expertise-based clinical research services to worldwide pharmaceutical, biotechnology, and medical device companies. We serve some of the best-known companies and work with many of the most advanced drugs, biologics, diagnostics, and medical devices in development today.Founded in 2004, Everest has grown from a small biometrics consultancy into a leading full-service CRO with more than 700 employees and over 100 active clients worldwide. Our continued success is driven by high-quality deliverables, exceptional client service, and a culture of flexibility and innovation. Quality is our backbone, customer-focus is our tradition, flexibility is our strength…that’s us…that’s Everest. Everest’s headquarters is located in Markham (Greater Toronto Area), Ontario, Canada. We have additional offices around the world: United States; Bulgaria; Poland; Romania; Croatia; China; and Taiwan. We also have remote employees across the globe. To drive continued success in this exciting clinical research field, we are seeking committed, skilled, and customer-focused individuals to join our winning team as a Statistical Programmer I or our Markham, Ontario on-site location, or remotely from a home-based office anywhere in the Canada in accordance with our Work from Home policy. Accountabilities: Statistical Programming: Under supervision, may develop and review SDTM and ADaM dataset specifications, annotated Case Report Forms (CRF) and other related documents (e.g., define.xml, reviewer’s guide) based on Statistical Analysis Plan (SAP), Everest company Standard Operating Procedures (SOPs) and Working Instructions (WIs), industry data standards, regulatory requirements, and trial Sponsor-specific requirements. Program and validate SDTM and ADaM datasets following approved dataset specifications; perform CDISC conformance checks on generated SDTM and ADaM datasets and address conformance findings. Develop SAS programs to generate and validate statistical output reports of trial data based on the SAP and TLGs mock-up shells. Provide statistical programming support to Clinical Study Reports, clinical trial efficacy and safety data integrations (Integrated Summary of Safety and Integrated Summary of Efficacy), as well as other data analysis and reporting needs such as regulatory required safety reports (e.g. Development Safety Update Report, 120 Day Safety Update, etc.), ad-hoc requests, and exploratory data analyses. 2. Clinical Data Acquisition and Cleaning Support: Develop and maintain SAS programs to perform database integrity checks and work with Data Managers to address data issues and queries for ongoing data cleaning and review. Support data acquisition of non-CRF data by developing SAS programs to reconcile the CRF and non-CRF data and performing data integrity checks of the non-CRF data. Develop SAS programs to generate data listings, summary tables, and graphs for ongoing data cleaning and scientific data surveillance reviews (safety, missing data, trending and signaling, etc.). Develop SAS programs to generate Patient Profiles to support trial subject case review activities. Document data and programming information in accordance with Everest company SOPs and WIs; and achieve audit readiness during and at the end of the clinical trials for internal and external quality and compliance audits. Achieve a high rating for each of the defined Everest company and trial Sponsor-specific statistical programming key performance indicators. Maintain current knowledge of pharmaceutical clinical research industry standards, conventions, and regulatory requirements, as well as the knowledge of clinical trial Sponsor-specific requirements when applicable. Comply to Everest company-specific and clinical trial Sponsor-specific training requirements. Develop and provide expertise in other programming and system administration areas when required. Requirements: A Master’s or Ph.D. Degree in statistics, biostatistics, epidemiology, public health, bioinformatics, mathematics, or computer sciences, with SAS certified Base/Advanced. Clinical trials programmers are highly preferred; exposure/experience in clinical trial statistical programming and/or data analysis is desirable.