Scientific Director, Pharmaceutical Development Analytics

Neurocrine Biosciences • San Diego, CA

6d

About The Position

The Scientific Director, CMC Quantitative Sciences is a senior technical individual contributor responsible for designing and advancing data-driven development and lifecycle management initiatives for drug products, including knowledge management, through application of advanced statistical analysis, experimental design, and quantitative modeling. Embedded within Pharmaceutical Development, this role serves as the portfolio-level statistical authority supporting drug product development programs from post-Proof of Concept through regulatory submission and the commercial lifecycle. In addition to serving as a quantitative authority, this role actively supports formulation and process development strategy by integrating statistical and mechanistic understanding of product design (at first principles-level) to optimize formulations for performance, stability and manufacturability, and strengthen process robustness. The Director partners cross-functionally with Pharmaceutical & Analytical Development, Quality, Regulatory CMC, and Commercial Manufacturing & Supply Chain to ensure that development and manufacturing decisions are supported by rigorous statistical analysis and defensible interpretation of CMC data. This role provides technical leadership across multiple development programs, strengthening process understanding, enabling robust control strategies, and improving the quality and regulatory defensibility of CMC submissions. While embedded in Pharmaceutical Development, the position influences programs spanning late-stage development through commercial lifecycle management and serves as a technical authority and mentor for quantitative approaches across CMC functions.

Requirements

• PhD, PharmD, or MS in Statistics, Chemical Engineering, Pharmaceutical Sciences, or related quantitative discipline
• 12-15+ years of experience applying statistical analysis to pharmaceutical development or manufacturing at all stages of development
• Demonstrated expertise in:Design of Experiments (DoE), multivariate analysis, process capability and variability analysis, statistical modeling of manufacturing processes
• Working knowledge of formulation principles and solid oral dosage formulation and unit operations (e.g., granulation, blending, encapsulation, compression, coating) required.
• Hands-on experience is strongly preferred
• Experience supporting late-stage development and regulatory submissions (IND/IMPD/CTA/NDA/BLA/MAA)
• Proficiency with analytical platforms such as JMP, R, Python, or equivalent statistical tools
• Strong ability to influence cross-functional teams through technical expertise and data interpretation

Nice To Haves

• Hands-on experience is strongly preferred

Responsibilities

• Owns drug product design and development strategy
• Generates, maintains and leverages process understanding and development data
• Informs control strategy for regulatory submission and hands-off to commercial
• Provides advanced statistical analysis and modeling expertise across CMC programs
• Translates complex development and manufacturing data into actionable technical insights
• Ensures statistical rigor and regulatory defensibility of CMC data packages
• Serves as a technical authority for statistical interpretation across lifecycle stages
• Supports formulation and process development strategies through data-driven insights and mechanistic interpretation
• Supports troubleshooting efforts and root-cause investigations as needed on both the formulation and process development fronts for development and commercial assets
• Apply multivariate tools to support identification of CMAs, CPPs, and design space boundaries
• Serve as a technical authority for complex data interpretation across CMC programs
• Provide statistical guidance for investigations involving process variability.
• Support root cause analysis of complex development or manufacturing trends
• Integrate datasets across development, analytical, and manufacturing functions to generate actionable insight
• Translate experimental data into formulation and process understanding, including identification of critical material attributes, excipient functionality, and process sensitivities
• Support development teams in interpreting DoE outcomes to refine formulations and unit operations (e.g., granulation, blending, compression, coating)
• Partner with Pharmaceutical Development scientists to design and optimize formulations using structured experimental approaches (DoE, mixture designs, response surface methods)
• Provide quantitative and mechanistic input into selection of excipients, formulation composition, and process parameters
• Support development and scale-up of key unit operations (e.g., fluid bed granulation, roller compaction, blending, tableting, coating) through data-driven modeling and risk assessment
• Guide process characterization strategies, including definition of parameter ranges, interaction effects, and scale dependencies
• Contribute to development of robust manufacturing processes by linking material attributes, process parameters, and product performance
• Support assessment of formulation and process robustness, including sensitivity analyses and failure mode identification
• Serve as a primary statistical authority supporting CMC regulatory submissions (NDA, BLA, MAA)
• Ensure statistical methodologies used in development and validation are regulatory defensible and aligned with ICH guidelines (Q8, Q9, Q10, Q14)
• Provide statistical interpretation for process validation strategies and control strategy justification
• Support responses to regulatory questions related to CMC data analysis and statistical methodology
• Contribute to justification of formulation composition, process design, and design space within regulatory filings
• Strengthen quantitative capabilities across Pharmaceutical Development
• Drive adoption of modern data science and modeling approaches that improve development efficiency and process understanding
• Establish best practices for experimental design and statistical analysis in development programs
• Mentor scientists on statistical thinking and interpretation of experimental results
• Promote integration of statistical and formulation/process science to enable more predictive and efficient development approaches

Benefits

• retirement savings plan (with company match)
• paid vacation, holiday and personal days
• paid caregiver/parental and medical leave
• health benefits to include medical, prescription drug, dental and vision coverage

What This Job Offers

• Job Type: Full-time
• Career Level: Senior