Senior Manager, Statistical Programming

The Senior Manager, Statistical Programming at Invivyd is responsible for leading statistical programming efforts, managing CROs, collaborating with teams to ensure data accuracy, and developing strategic programming plans. This includes overseeing regulatory submission activities, creating and validating SDTM, ADaM, and TLFs, and ensuring compliance with industry standards.

To qualify for the Senior Manager, Statistical Programming role at Invivyd, candidates should possess a BS in Statistics, Biostatistics, or a related field, along with over 8 years of experience in statistical programming. Excellent SAS programming skills, experience with regulatory submissions, knowledge of CDISC standards, and a strong understanding of clinical trial processes are also required.

The Senior Manager, Statistical Programming position at Invivyd requires excellent SAS Software programming skills, including proficiency in Base SAS, SAS/STAT, SAS/GRAPH, and macro development. SAS Certification is also necessary to ensure candidates meet the high standards expected in this role.

At Invivyd, career growth is highly encouraged. The company fosters an environment of continuous learning and offers opportunities for professional development in statistical programming, regulatory standards, and collaborative projects that advance individual skills while contributing to the company's mission.

Yes, the Senior Manager, Statistical Programming position at Invivyd is primarily remote, although preference will be given to candidates who are located in the Boston area. This flexibility supports work-life balance while allowing team members to collaborate effectively.

When answering this question, highlight specific projects where you utilized SAS for regulatory submissions. Include details about your role in data analysis, handling of ADaM and SDTM datasets, and how you ensured compliance with relevant regulations.

Discuss your approach to managing CROs by emphasizing the importance of regular communication, setting clear expectations, and using project management tools to track timelines and metrics, ensuring all data collected meets high standards of integrity.

Explain any obstacles you encountered, such as timeline delays or resource limitations. Focus on how you overcame these challenges by adapting your strategies, collaborating with other teams, or leveraging your technical skills in statistical programming.

Share your experience with CDISC standards, specifically mentioning any projects where you defined or implemented CDISC compliant SDTM and ADaM datasets. Detail how your knowledge ensured regulatory compliance and improved the quality of clinical data.

Discuss specific clinical trials you have worked on, detailing how you tracked milestones and worked with vendors for statistical reporting deliverables. Explain any systems or processes you implemented to enhance tracking efficiency.

Explain your step-by-step approach to validating macros, including testing, writing documentation for reusability, and ensuring they meet analysis requirements. Emphasize the importance of maintaining a high standard for documentation for future reference.

When answering this question, focus on a specific incident, what you learned from it, and the corrective steps you took. This showcases your resilience and commitment to improving processes and outcomes in statistical programming.

Identify a key regulatory requirement, such as compliance with ICH/GCP guidelines, and explain its importance. Discuss how you ensure that your statistical programming work aligns with these regulations to uphold the integrity of your submissions.

Describe your communication style, providing examples of collaborations with medical, data management, and project management teams. Highlight the importance of fostering open dialogue and shared goals to enhance project success.

Share your passion for data analysis and how it contributes to improving patient outcomes. Reflect on your excitement for innovative drug development and your commitment to leveraging your statistical programming skills to make a real difference.