Senior Manager, Statistics (Onsite; hybrid)

This positions sits onsite 3 days weekly (2 days remote) at one of the following locations: Worcester, MA; Cambridge, MA; North Chicago, IL; Irvine, CA; South San Francisco, CA.

Purpose:

The Senior Manager, Statistics provides statistical leadership to support the research and development organizations for drug discovery, target identification/verification, non-clinical and clinical biomarker exploration to characterize subgroups of patients or markers of disease progression and treatment response for precision medicine. The senior manager works independently in partnership with discovery researchers, translational scientists and clinicians in the design, collection, analysis and reporting of multi-dimensional biomarker data from Discovery to late-stage clinical development to enable objective decision-making for each drug development program.

Responsibilities:

· Provide statistical leadership in partnership with translational biomarker scientists and clinicians in the design, analysis and reporting of biomarker and assay studies in association with clinical trials, including pharmacodynamic/safety biomarker analyses, prognostic/predictive biomarker identification and development, bioassay and companion diagnostic test development, patient subgroup identification based on biomarkers and clinical variables. Support biomarker related responses during regulatory interactions and biomarker related product life-cycle management strategy planning and implementation

· Drive for scientific excellence in designing, analyzing and reporting of biomarker-based clinical trials or other scientific research studies. Independently developing biomarker section of clinical trial protocols or biomarker analysis plans. Work independently to implement sound statistical methodology in scientific investigations.

· Providing statistical leadership in partnership with scientists in discovery and translational science units in the design, analysis and reporting of in vitro, in vivo pharmacology studies, and human clinical trials. Identify markers and signatures from internal/external omics/imaging and other biomarker data for target identification, mechanism of action, resistant mechanism, disease progression, patient selection and stratification for precision medicine.

· Full accountability for data collection/integrity, and statistical analyses as per the biomarker analysis plan. Identifying and anticipating issues arising in the study design; conducting and proposing scientifically sound approaches. Evaluating appropriateness of available software for planned analyses and assessing needs for potential development of novel statistical methodology.

· Improving data presentation and inference with additional statistical and business insights. Collaborating in publication of scientific research. Ensuring that study results and conclusions are scientifically sound, clearly presented, and consistent with statistical analyses provided. Clearly explaining statistical concepts, enabling non-statisticians and biomarker collaborators to use existing tools and interpret results better.

Qualifications:

· MS (with 8+ years of experience) or PhD (with 4+ years of experience) in Statistics, Biostatistics, or a highly related field, with some applied consulting or research experience on topics related to pharmaceutical research, bioinformatics, target identification, biomarkers, and subgroup identification.

· High degree of technical competence and effective communication skills, both oral and written

· Able to identify data or analytical issues, and assist with providing solutions by either applying own skills and knowledge or seeking help from others

· Able to build strong relationship with peers and cross-functional partners to achieve higher performance. Highly motivated to drive innovation by raising the bar and challenging the status quo

· Have strong leadership skills and experience in working/managing cross-cultural or oversea teams

· Pharmaceutical or related industry knowledge desired, including experience and understanding of drug development and life-cycle management in the regulated environment.

· Able to integrate high dimensional data from different sources. Familiar with overfitting and multiple testing control methods, such as cross-validation and random resampling techniques. Familiar with machine learning and predictive modeling methods.

AbbVie is committed to operating with integrity, driving innovation, transforming lives, serving our community, and embracing diversity and inclusion. It is AbbVie’s policy to employ qualified persons of the greatest ability without discrimination against any employee or applicant for employment because of race, color, religion, national origin, age, sex (including pregnancy), physical or mental disability, medical condition, genetic information, gender identity or expression, sexual orientation, marital status, status as a protected veteran, or any other legally protected group status.