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The BioMarin Summer Internship Program will enable students to gain valuable experience and knowledge of the processes and systems within BioMarin, while gaining an insight into the pharmaceutical/biotech industry. Over the course of 10 - 12 weeks our interns gain industry experience while working alongside our talented team on meaningful projects. Statistical Science, a function of BioMarin Data Science, provides statistical expertise and leadership in the design and execution of Phase 1-4 clinical trials. This includes the analysis, interpretation, and reporting of trial data to support clinical development, medical affairs, market access, and scientific publications across the lifecycle of therapeutic products.Statistical Science works closely with Clinical Science, Pharmacovigilance, Regulatory Affairs, Market Access, Medical Affairs, as well as Data Analytics Science and Data Management Science to achieve these objectives.
Job Responsibility:
Work closely with senior members of the Statistical Science function on research and application of Bayesian mixed effect models for clinical data
Explore approaches for historical data augmentation in trial settings
Work on seamless Phase2/3 design including sample size re-estimation and alpha adjustment, run simulation to assess statistical operating characteristics of a seamless design
Have opportunities to gain hands-on experience in innovative statistical methodologies applied to real clinical study design and data analysis
Present project achievements to the Statistical Science function at the end of the summer
Requirements:
Proficiency in SAS, and/or R, and/or Python
Solid understanding of Bayesian methods and mixed-effects modelling
Knowledge of historical data augmentation and adaptive or seamless trial design (sample size re-estimation, alpha adjustment)
Strong ability to conduct methodological research, strong problem-solving skills
Strong communication skills and ability to work independently and collaboratively
PhD candidate in Statistics, Biostatistics, or related field
Must be available to work full-time, 40 hours a week
Must be currently enrolled as a full-time student at an accredited U.S. based university or college and enrolled in the fall term after the completion of the internship OR have graduated within 1 year of the start of the program
Nice to have:
Strong knowledge of Bayesian methods, mixed effect models, and adaptive design
Familiarity with sample size re-estimation and alpha adjustment preferred
What we offer:
Paid hourly wage, paid company holidays, and sick time
Apply skills and knowledge learned in the classroom to on-the-job experiences
Comprehensive, value-added project(s)
Develop skills specific to your major
Opportunities for professional development by building relationships and learning about other parts of the business
Participate in company all hands meetings, monthly community lunches
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