Lead Statistical Programmer

Job Description

• The Lead Statistical Programmer at Recor Medical is a key role responsible for driving statistical programming activities. • This position involves developing and implementing statistical programming strategies, ensuring compliance with regulatory requirements, and fostering collaboration with cross-functional teams. • Key responsibilities include leading programming activities, providing technical expertise, contributing to process improvement initiatives, and ensuring the accuracy, integrity, and timeliness of statistical programming deliverables. • The Lead Statistical Programmer also plays a crucial role in staying updated with advancements in open-source statistical programming methodologies and technologies. • Overall, this position requires strong leadership, technical proficiency, and a dedication to maintaining the highest standards of quality and compliance in statistical programming.

Qualifications

• A minimum of a master’s degree in statistics, biostatistics, computer science, mathematics, or a related field. • At least 5 years of experience managing statistical programming within the medical device or pharmaceutical industry. • Previous experience in leading or managing a team of statistical programmers is highly desirable. • Strong proficiency in statistical programming languages such as SAS and R. • Experience with open-source statistical programming languages such as R is highly desirable. • Familiarity with open-source statistical software packages and tools commonly used in clinical research. • Experience with open-source submission platforms and formats, such as RMarkdown for regulatory submissions, is advantageous. • Familiarity with regulatory requirements and guidelines (e.g., FDA, ICH) for clinical trials and submissions. • Experience in developing and implementing statistical programming strategies for clinical studies. • Knowledge of Clinical Data Interchange Standards Consortium (CDISC) compliance, Study Data Tabulation Model (SDTM) and the Analysis Data Models (ADaM) for regulatory submissions is desirable. • Prior involvement in regulatory submissions (e.g., IDEs, PMAs) using open-source tools and platforms is advantageous.

Benefits

• Oversee external statistical programming vendors services, including communication, guidance, monitoring, and issue resolution. • Serve as the subject matter expert for the Data Visualization Team, guiding the creation of clinical programming listings, metric reports, and departmental dashboards. • Develop and implement statistical programming strategies to support the design, analysis, and reporting of clinical studies and regulatory submissions. • Collaborate with cross-functional teams including biostatisticians, project management, clinical data managers, scientific affairs, medical affairs, and regulatory affairs to ensure timely and accurate delivery of statistical programming deliverables. • Review and contribute to study protocols, statistical analysis plans, CRF design, eCRF annotations and data specifications to provide input to Clinical Project and Data Management Team for analysis needs. • Provide technical expertise in statistical programming methodologies and ensure adherence to industry standards and regulatory requirements (e.g., FDA, ICH guidelines). • Oversee the development, validation, and maintenance of statistical analysis datasets and programming codes for clinical trials. • Review and QC statistical outputs, tables, listings, and figures generated by the statistical programming team to ensure accuracy and consistency. • Act as a subject matter expert in statistical programming for regulatory interactions and contribute to the preparation of regulatory submissions (e.g., IDEs, PMAs). • Stay abreast of advancements in statistical programming methodologies and technologies and assess their potential application within the organization. • Participate in process improvement initiatives to enhance efficiency, quality, and compliance within the statistical programming function. • Other duties as assigned.