Remote, 12-month contract with extension possible
As the Lead Biomarker Statistician, you will be responsible for ensuring that biomarker data are generated appropriately to address relevant objectives such as the estimation of biological effects or the projection of clinical outcomes. This includes ensuring that studies are designed to answer specific and pertinent questions, that the analyses performed to account for various sources of variability and that the conclusions drawn are robust in the presence of multiplicity and confounding factors, especially as many biomarkers are multidimensional or may be an indirect measure of the clinical outcome. The Lead Biomarker Statistician will ensure sound statistical thinking and methodologies are utilized in the design, analysis and statistical interpretation of studies focused on biomarkers and exploratory endpoints. Studies will include those support drug target discovery, target validation and confidence in rationale, and precision medicine in early-stage clinical trials. You will have broad responsibility and contribute at early stages during pre-clinical development as well as across our therapeutic areas. Use your hard-earned biostatistics analytical and strategic skills to help us achieve our mission of saving lives by curing these diseases.
Goals will include:
- Integrate biomarkers across clinical trials in order to summarize and draw insightful inferences to help further advancing the drug development programs by using appropriate statistical techniques such as propensity score matching and meta-analysis
- Lead in development and adaptation of new statistical methodologies in support of drug development
- Conduct analyses on biomarker data and develop summaries by implementing appropriate statistical methodologies and data visualizations
- Collaboration with internal and external partners in the optimized clinical study design, end point selection and sample size calculations, analysis, interpretation, and publication of clinical trial data
- Execute protocols, statistical analysis plans, study reports, ensure statistical integrity of presentations and publications of clinical studies by applying your past experience
- Participate in establishing and maintaining policies, standards and guidance for Biostatistical operations
- Lead Biometrics & Digital Science Department Initiatives
- Support clinical study team including but not limited to generation of data visualizations and summary reports to support internal decision-making
- Participate in regulatory interactions (IND/CTA filings, annual safety reporting) and responsible for biostatistics input into study protocols and clinical study reports
- Review study randomization specifications, oversee outsourced development of analysis data and results; and reviewing case report forms while managing workflow to ensure quality, prioritization, and timeliness across multiple programs
- Manage external vendors and serve as a key Biostats liaison with external organizations
- Ensure up to date knowledge of industry and academic developments in the Neuroscience, Immuno-Oncology and Orphan disease fields and apply to clinical study design and analysis
- PhD with 7+ years, or MS with 8+ years of proven experience in the Pharmaceutical/biotech industry.
- Strong knowledge of theoretical and applied statistics
- Experience with multivariate statistics and statistical methods to quantify uncertainty in multi-dimensional data; experience running simulations and mixed models
- Hands on ability to drive and lead statistical strategies for clinical development of drug candidates from first-in-human testing to all later phases of clinical investigation, including pivotal Phase 2/3 studies and NDA/BLA submissions
- Demonstrated success leading the statistical strategy, analysis and design of a clinical development program
- Knowledge of applicable regulatory rules and guidelines, e.g., ICH, GCP, HIPAA
- Advanced programming skills in SAS and/or R and other relevant statistical software solutions. Ability to code programs designed to analyze and report complex clinical trial data, as well as for electronic review, exchange, transformation and submission of data in CDlSC, SDTM and ADaM formats
- Working knowledge of GitHub and Markdown preferred.
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