Lead Statistical Programming Manager

ABBVIE; South San Francisco (CA); On-site; USD 110,000 - 209,000; Full time

Benefits offered by this job

Paid time off

Medical/dental/vision insurance

401(k)

Long-term incentive programs

Job summary

AbbVie in South San Francisco is seeking a Manager of Statistical Programming to lead a team of programmers in early development. You will interface with Statistics, Data Sciences, Medical Writing, Regulatory Publishing and Clinical Operations to guide programming strategy and deliver high-quality ADaM datasets and TLFs.

The ideal candidate holds an MS or BS in a related field with extensive SAS and CDISC experience, strong communication skills, and a proven ability to mentor staff within

Qualifications

• Experience leading a team of statistical programmers.
• Deep expertise in SAS programming for ADaM datasets.
• Strong understanding of CDISC standards and regulatory filings.

Responsibilities

• Leads statistical programming activities for a compound/indication in early development.
• Manages a team of programmers and resource planning for staff.
• Ensures timely deliverables and adherence to quality processes.
• Develops SAS programs for ADaM datasets following CDISC standards.
• Creates Tables, Listings and Figures and ensures data set consistency.
• Prepares regulatory documentation and data definition docs.
• Oversees development of SAS Macros and SOPs.
• Mentors assigned programmers and analysts.

Skills

Team leadership

SAS programming

CDISC standards

Cross-functional collaboration

Effective communication

Education

MS in Statistics, Computer Science or related field

BS in Statistics, Computer Science or related field

Tools

SAS

CDISC knowledge

Job description

AbbVie in South San Francisco is seeking a Manager of Statistical Programming to lead a team of programmers in early development. You will interface with Statistics, Data Sciences, Medical Writing, Regulatory Publishing and Clinical Operations to guide programming strategy and deliver high-quality ADaM datasets and TLFs.

The ideal candidate holds an MS or BS in a related field with extensive SAS and CDISC experience, strong communication skills, and a proven ability to mentor staff within