Senior Research Statistician, Discovery and Exploratory Statistics (DIVES), AbbVie Bay Area
AbbVie is expanding its oncology hub on the West Coast, with the new AbbVie Bay Area site located at South San Francisco focused on the discovery and development of novel oncology therapies. More than 1,000 AbbVie scientists, clinicians, and product developers with strong entrepreneurial roots work across these three sites. 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.
Discovery and Exploratory Statistics (DIVES) is part of the Data and Statistical Sciences (DSS) organization in AbbVie R&D. This group located on the West Coast provides statistical expertise for various groups in drug discovery, precision medicine and development sciences in early phase oncology clinical trials. Examples of applications/topics supported include in vitro screening, in-vivo pharmacology, genomics, proteomics, imaging, and other biomarker data generated from pre-clinical and clinical studies.
The Senior Research Statistician, DIVES position works with discovery researchers, translational scientists, DMPK scientists and clinical biomarker leads in the design, collection, analysis and reporting of multi-dimensional biomarker data from Discovery to early-stage clinical development to enable objective decision-making for each drug development program. This position will be based at AbbVie Bay Area location.
- Collaborating with discover and translational biomarker scientists and clinicians and contribute to design, analysis and reporting of biomarker and assay studies in association with early and late phase clinical trials. The typical analysis includes pharmacodynamic biomarker analysis, safety biomarker analysis, prognostic and predictive biomarker identification and development, bioassay and companion diagnostic test development, patient subgroup identification based on biomarkers and clinical variables.
- Contributing to design, analysis and reporting of biomarker-based clinical trials or other scientific research studies. Assist in developing biomarker section of clinical trial protocols or biomarker analysis plans. Working under supervision to implement sound statistical methodology in scientific investigations.
- Ensuring data are sensible and comprehensive with quality for the assigned statistical analysis and deliverables.
- Supporting and advising scientists in discovery and translational science units in the design, analysis and reporting of in vitro, in vivo pharmacology studies, and human clinical trials under supervision. 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.
- With Supervision perform statistical analyses as per the biomarker analysis plan. Bringing attention to supervisor and team for potential issues arising in the study design; conducting and proposing scientifically sound approaches. If assigned, evaluating appropriateness of available software for planned analyses and assessing pros and cons for potential development of novel statistical methodology.
- Accountability for data presentation and inference, with supervision. 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 to non-statisticians. Provide responses to questions and pursue analyses suggested by data under supervision. Supporting communications between assigned product team(s) and functional management.
- MS (with 4+ years of experience) or PhD (with 0+ years of experience) in Statistics, Biostatistics, or a highly related field.
- 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 collaborators to achieve higher performance. Highly motivated to drive innovation by raising the bar and challenging the status quo
- 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.
Significant Work Activities: N/A
Job Type: Experienced