Senior Manager, Statistical Programming
Pharmacyclics is committed to the development and commercialization of novel therapies intended to improve the quality and duration of life and to resolve serious unmet medical needs for cancer patients. Pharmacyclics is a wholly-owned subsidiary of AbbVie (NYSE:ABBV), a global, research-based biopharmaceutical company. Oncology is a key therapeutic area for AbbVie, with a portfolio consisting of three marketed products and a pipeline containing multiple promising new molecules that are being studied in more than 200 clinical trials for over 20 different types of cancer.
More than 1,200 Pharmacyclics and AbbVie research scientists, clinicians, marketing, operations and corporate professionals work in the San Francisco Bay Area. They combine their expertise in immuno-oncology, stem cells, and cell-signaling with their knowledge of bispecific antibodies, antibody-drug conjugates (ADCs), and covalent-inhibitor technologies to discover and develop novel cancer treatments. Together, we are striving to outsmart cancer.
General Position Summary/Purpose:
Manage and coordinate the Statistical Programming staff to ensure efficient use of the resource and work flow
Designs, develops, evaluates and modifies computer programs to analyze and evaluate clinical data. Generate Study specific and ad-hoc clinical data listings, summary tables and figures.
Key Accountabilities/Core Job Responsibilities:
- Manage Lower level personnel.
- Performs data analysis using primarily the SAS programming language for the summary and interpretation of clinical trial data.
- Create CDISC SDTM and ADaM files, SAS export files and Define.xml use for Electronic Submission from the data received in non-standard form from various sources.
- Performs Data analysis, statistical analysis, generate safety and efficacy tables, listings and graphs using Base SAS, SAS Macros, SAS/STAT, SAS/Graph, SAS/SQL and SAS/ODS.
- Review Data Management Plan, Data validation plan and edit check specifications
- Interact with Statisticians and other clinical team, perform ad hoc analysis and generate outputs according to the requirements.
- Implements and contributes to statistical analysis plans; provides additional expertise in the analysis of clinical trial as it relates to protocol development, case report form design and data collection.
- Recognizes inconsistencies and initiates resolution of data problems.
- Acts as a liaison between statistical programming, subcommittees and project teams as needed.
- Exercises independent judgment in developing methods, techniques and evaluation criteria for obtaining results.
- Works on significant and unique issues where analysis of situations or data requires evaluation of intangibles.
- May serve as external spokesperson for the organization.
- Acts independently to determine methods and procedures on new assignments.
- May provide guidance to other lower level personnel.
- Works closely with Biostatistics to create analysis files specifications following the instructions provided in Statistical Analysis Plan (SAP)
- Develop SAS coding and table templates for preparing, processing and analyzing clinical data.
- Create/acquire tools to improve programming efficiency or quality.
- Establish monitoring of data transfers for ongoing trials to identify study conduct or data quality issues.
- Experience with integrated summaries (ISE/ISS) and Clinical Study Reports.
- Ability to use professional concepts to achieve objectives in creative and effective ways.
- Experience in the analysis of complex Oncology clinical trial data.
- Experienced in managing programming staff.
- Solid knowledge of CDISC standard (SDTM & ADaM).
- Minimum 12 years Pharmaceutical/Biotech programming experience with minimum 3 years management experience.
- NDA submission experience is a plus
- Strong SAS programming and Statistical background along with experience with SAS Base, SAS/Macros, SAS/Graph and SAS/Stat.
Education Requirements (degree, certifications, etc.): Include must have and preferred
- BS/MS in Statistics, Math or Scientific Discipline.