Associate Director, Quantitative Science
Who We Are
For more than two decades, going our own way has led to countless breakthroughs, bettering the lives of those suffering from rare genetic disease. In 1997 we were founded to make a big difference in small patient populations. Now we seek to make an even greater impact by applying the same science-driven, patient-forward approach that propelled our last 25 years of drug development to larger genetic disorders, as well as genetic subsets of more common conditions. Through our unparalleled expertise in genetics and molecular biology, we will continue to develop targeted therapies that address the root cause of the conditions we seek to treat. Applying our knowledge to make a transformative impact is not just a calling, but an obligation to those who will benefit most. The end goal has always been better lives and now we can reach more.
And the more people we reach, the more our impact can grow. We transform lives through genetic discovery.
Our desire to make a positive impact on our patients extends to our employees and BioMarin is committed to fostering an inclusive environment where every person feels seen, valued, and heard – so employees can thrive in all areas of their lives, in and outside of work. We seek to provide an open, flexible, and friendly work environment to empower people and to provide them with the ability to develop their long-term careers. Ultimately, we want to be an organization where people enjoy coming to work and take pride in our efforts to help patients.
The Associate Director Quantitative Science (Post-Approval) is a self-sufficient and high-impact position focusing on supporting the statistical needs in the post-approval area in terms of rapid response for critical requests, exceptional communication and collaboration abilities, a broad practical perspective on contributing to the success of medical affairs and market access efforts, and technical leadership in formulating, interpreting, and communicating statistical approaches.
Specifically, the applicant must have demonstrated the following qualifications.
- Subject matter expert in related technical areas such as real-world data/evidence (RWD/E), patient centric outcomes (PCOs), health economics and outcomes research (HEOR), and contemporary statistical modeling techniques (e.g., prognostic / predictive modelling, indirect treatment comparison, Bayesian analysis, etc.).
- Proficient data science analytical and programming skills.
- Excellent matrix team leadership and interpersonal skills.
The position’s primary responsibilities will include the following
- Leading a Data Science project team.
- Directing / supporting all statistical activities from design to ad-hoc analysis to reporting and presentation.
- Performing all tasks from statistical thinking to programming.
- Functions as a statistical / analytical subject-matter expert in all post-approval areas, especially Medical and Market Access / HEOR.
- Ensures creative and effective statistical methodologies are identified and implemented in designs, analysis plans, and reporting and interpretation of post-approval study outcomes and statistical analyses.
- Provides operational statistical leadership for the post-approval study team’s and Market Access team’s statistical needs in HEOR, health technology assessments (HTAs), price negotiation and reimbursement dossiers, observational research, and other medical and scientific communication activities.
- Collaborates effectively with internal stakeholders from Clinical Development, Medical Affairs, HEOR, and RWE teams and external stakeholders (e.g., regulators, payers, review boards, co-authors, CROs, etc.).
- Works proactively and efficiently with the Quantitative Science leads, Clinical Development statistical leads, and other colleagues within Data Science to organize, plan, manage, and control deliverables against goals and timelines.
- Serves as the lead for the Data Analysis Working Group (DAWG), Data Analysis and Reporting Team or Statistical Analysis Review Team (DART) for a therapeutic area (TA) or a program.
- Contributes to clinical study reports (CSRs) and related periodic reports, and to authoring or co-authoring methodological or study-related presentations, posters, and manuscripts.
- Understands modern drug discovery, research, development, and post-approval principles and processes.
Education & Experience
M.S. in Biostatistics, Statistics, Data Science, Pharmacoeconomics, or similar field required.
Ph.D. in Biostatistics, Statistics, Data Science, Pharmacoeconomics, or similar field preferred.
A minimum of 5 (PhD) – 7 (Master’s) years’ experience in pharmaceutical and/or biotech industry.
- at least 3 (PhD) - 4 (Master’s) years of working experience in post-approval, RWE, or market access/HEOR areas.
- Must be able to effectively collaborate with cross-functional teams in the realization of clinical programs and initiatives from study design to presentation of results.
- In-depth knowledge of Market Access / HEOR statistical needs and statistical methodology, as well as hands-on data analysis experience.
- Must be able to provide technical and tactical support for cross-functional Medical Affairs and Market Access / HEOR programs including registries, burden of Illness / natural history of disease for regulators, payers, and clinicians.
- Must be able to work effectively in a constantly changing, diverse, and matrix environment.
- Advanced knowledge of theoretical and applied statistics or other related data sciences.
- In-depth knowledge of statistical analysis methods, especially on data originated from post-approval areas, especially Medical Affairs and Market Access / HEOR.
- Solid programming skills including SAS, R, Python and other statistical software packages.
- Ability to lead, motivate, and mentor internal and contract staff.
- Must be able to effectively review documents drafted by staff.
- Must be knowledgeable of FDA, EMA and ICH regulations and guidelines.
- Must be knowledgeable about HEOR / HTA requirements and guidelines.
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.