Sr. Manager/Associate Director, Quantitative Science

BioMarin Pharmaceutical Inc.•San Rafael, CA

96d

About The Position

The Quantitative Science team at BioMarin performs statistics and data science across research and development and beyond. As the Senior Manager or Associate Director of Quantitative Science, you will assume the role of a statistician/data scientist and play a pivotal role in supporting different functional areas. This influential and self-sufficient position will make significant contributions to drug discovery, nonclinical research, preclinical research, experimental medicine, biomarker development, clinical development, post-approval/medical areas, real-world data/real-world evidence (RWD/RWE), genomics, business development, and manufacturing. Your primary responsibility will be to ensure excellence in the design, analysis, interpretation, and communication of data. Additionally, you will actively engage with counterparts to foster collaboration and champion the use of quantitative thinking. The ideal candidate must demonstrate the following qualifications: Broad subject matter expertise in statistics and data science with hands-on experience in application in diverse areas Proficiency in statistics, advanced data science, and programming Ability to develop fit-for-purpose statistical methodologies and software tools is a plus Exceptional communication/interpersonal skills

Requirements

M.S. in Biostatistics, Statistics, Data Science, or similar field required.
Ph.D. in Biostatistics, Statistics, Data Science, or similar field preferred.
Years of experience in pharmaceutical and/or biotech industry: A minimum of 5 (PhD) or 7 (Master’s) for associate director; A minimum of 2 (PhD) or 4 (Master’s) for senior manager.

Nice To Haves

Basic broad knowledge of the research, development, and associated areas in the pharmaceutical/biotechnology field
Broad knowledge of statistical methods and ability to solve problems creatively and pragmatically
Scientific curiosity and ability to learn
Exceptional consultative, conversational, written communication, presenting, collaborative, teaching, and interpersonal skills
Adaptability and ability to thrive in a dynamic, diverse, and matrixed environment
Hands-on knowledge of statistical methods applicable across research and development such as time-to-event analyses, analysis of covariance, mixed models for repeated measures, categorical data approaches, Bayesian methods, simulation approaches, artificial intelligence (AI) and machine learning (ML), graphical methods, etc.
Hands-on knowledge of study design and sample size calculation
Strong programming skills in at least two of SAS, R, or Python
Proficiency in or demonstrated ability to learn developing specifications and designing analysis modules to automate analysis, visualization, and reporting of standardized experiments; proficiency in documenting and supporting such systems
Demonstrated ability to lead, motivate, and mentor both internal and contract staff.
Effective review and evaluation skills for documents drafted by staff.

Responsibilities

Perform statistical experimental design, analysis, interpretation, and reporting, including for example
Estimate sample size and aid in study design including conducting simulations
Conceptualize solutions to unique challenges and develop analysis methods and analysis programs accordingly
Explore and develop the use of artificial intelligence (AI) and machine learning (ML)
Write statistical analysis reports and give presentations
Develop statistical applications that enable researchers to analyze repetitive experiments
Conduct outreach to internal functions, establishing collaborations and providing education to identify opportunities to apply statistics and data science that positively impact the business
Provide guidance and direction to junior staff on the team

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