Who We Are
From research and discovery to post-market clinical development, our WWRD engine involves all bench and clinical research and the associated groups that support those endeavors. Our teams work on developing first-in-class and best-in-class therapeutics that provide meaningful advances to patients who live with genetic diseases.
The Quantitative Science team at BioMarin promotes quantitative thinking and data-driven strategies for various aspects of the business, including research, early development, clinical trial monitoring, post-approval, and manufacturing.
As the Associate Director of Quantitative Science (Research & Other Areas), you will assume the role of a Statistician/Data Scientist and play a pivotal role in supporting different functional areas of drug research, development, and manufacturing. This influential and self-sufficient position will make significant contributions to drug discovery, preclinical studies, biomarker identification and development, and nonclinical research.
Your primary responsibility will be to ensure the appropriate design, analysis, interpretation, and communication of data. Additionally, you will actively engage with researchers to foster collaboration, promote the use of quantitative thinking, and encourage the utilization of artificial intelligence (AI) and machine learning (ML) techniques for problem-solving.
The ideal candidate must demonstrate the following qualifications:
- Subject matter expertise in applying statistics and problem solving in related areas
- Proficiency in statistics, advanced data science methods and application, and programming
- Experience in developing fit-for-purpose statistical methodologies and software tools
- Excellent matrix team leadership and interpersonal skills
- Lead the statistical support for experimental design, analysis, interpretation, and reporting of studies in research, biomarker development, manufacturing, and other areas
- Estimate sample size and aid in study design including conducting simulations
- Develop analysis methods and analysis programs
- Write and/or review statistical analysis reports
- Develop statistical algorithms and specifications for applications that enable researchers to analyze repetitive experiments
- Conduct outreach to internal functions, establishing collaborations and identifying opportunities to apply statistics and data science for business impact and problem solving
- Explore and develop the use of AI and ML for business impact and problem solving
- Provide guidance and direction to junior staff in the team
Education & Experience:
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.
- Knowledge in drug discovery process and relevant statistical applications
- Scientific curiosity and ability to learn
- Proven ability to effectively collaborate with cross-functional teams
- Strong consultation, conversational, written communication, and interpersonal skills
- Adaptability and ability to thrive in a dynamic, diverse, and matrixed environment
- Advanced knowledge of statistical methods for evaluating in vitro and in vivo studies, assay development and characterization, biomarker discovery, digital biomarkers, etc.
- Knowledge of advanced data science techniques such as artificial neural networks (ANN), natural language processing, and image analysis is a plus.
- Strong programming skills in SAS, R, Python, and other statistical software packages.
- Proficiency in developing specifications and designing analysis modules to automate analysis, visualization, and reporting of repetitive experiments
- Demonstrated ability to lead, motivate, and mentor both internal and contract staff.
- Effective review and evaluation skills for documents drafted by staff.
We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity, sexual orientation, national origin, disability status, protected veteran status, or any other characteristic protected by law.