Associate Director, Quality Data Science & Engineering

Allogene Therapeutics; South San Francisco (CA); On-site; USD 170,000 - 210,000; Full time

Benefits offered by this job

Annual bonus

Equity

Health insurance

Generous time off

Holiday company-wide shutdowns

Job summary

Allogene Therapeutics, headquartered in South San Francisco, CA, seeks an Associate Director, Quality Engineer/Data Science to lead the Quality Data Science/Quality Engineering function. You will embed applied statistics, data science, and machine learning to advance the Allogene CAR T platform and guide data-driven decisions across programs.

Based in South San Francisco, CA. The role partners with project teams to establish a lifecycle approach to product quality control, leveraging tools and

Qualifications

• BS/MS in Statistics, Data Science, or related field (advanced degree preferred).
• ASQ Quality Engineer certification preferred.

Responsibilities

• Develop and execute strategy to establish quality data science as a core capability for GMP operations.
• Provide input to project teams on applied science and statistics to drive product quality control and lifecycle management.

Skills

Applied statistics

DoE

Multivariate analysis

Regression

Time-series

Education

BS/MS in Statistics or Data Science

Tools

R

Python

JMP

SAS

Job description

About Allogene:

Allogene Therapeutics, with headquarters in South San Francisco, is a clinical-stage biotechnology company pioneering the development of allogeneic chimeric antigen receptor T cell (AlloCAR T) products for cancer and autoimmune disease. Led by a management team with significant experience in cell therapy, Allogene is developing a pipeline of “off-the-shelf” CAR T cell product candidates with the goal of delivering readily available cell therapy on demand, more reliably, and at greater scale to more patients.

About the role:

We are seeking a highly motivated Associate Director, Quality Engineer/Data Science to work in this exciting new area of allogeneic cell therapy. In this role, you will report to the head of Validation and Quality Engineering, and you will be responsible for developing and leading the Quality Data Science/Quality Engineering function to embed the principles and practices of applied statistics, data science and machine learning to further Allogene’s efforts in leading the establishment of an allogeneic CAR T platform, and to provide guidance and data driven insights across Allogene’s programs. You will work closely with respective project teams to establish a quality data science roadmap to implement a lifecycle approach for product quality control strategies, including tools and technologies to drive innovation and continuous improvement. The position is based out of our headquarters in South San Francisco, CA.

Responsibilities include, but are not limited to:

• Develop and execute strategy and roadmap to establish quality data science as a core capability for building allogeneic platform knowledge and establish data analytics to enable predict and prevent capabilities across GMP operations.
• Provide direction and input to project teams utilizing the principles of applied science and statistics to drive strategies for process and analytical understanding and overall product quality control, including approaches for product comparability, process validation, product monitoring, stability trending and lifecycle management/improvement.
• Contribute to the build out of the Allogene GMP Quality Management System by developing procedures and providing significant input and support to Product Quality Review and Management Review tools and practices.
• Serve as company authority on quality data science and QE activities in support of regulatory submissions and inspections, including assuring inspection readiness.
• Support root cause investigations and ensure data-driven decision making.
• Champion the use of data analytics and operational excellence tools to drive process improvement and innovation across the Allogene enterprise.
• Integral member of cross-functional teams to garner interdisciplinary insights (e.g. technical, clinical) to further accelerate Allogene’s leading approach to the establishment of an “off-the-shelf” allogeneic CAR T platform.
• Collaborate across functions and stakeholders to develop a Knowledge Management approach for Allogene.
• Routinely scan external environment and engage in industry forums to proactively identify and implement best practices and new technologies.

Position Requirements & Experience:

• BS/MS degree in Statistics, Data Science, or related field (advanced degree preferred), ASQ Quality Engineer certification preferred, with at least 6-8 years of relevant experience in the biotechnology or pharmaceutical industry.
• Strong expertise in applied statistics (e.g., DoE, multivariate analysis, regression, time‑series).
• Hands‑on experience with tools such as R, Python, JMP, SAS, or equivalent.
• Experience working with complex data from laboratory, process, or manufacturing systems and ability to translate complex data insights into actionable business recommendations.
• Familiarity with visualization tools.
• Comprehensive knowledge of GMP regulations, guidance, and industry best practices.
• Proven success influencing cross‑functional teams and senior stakeholders without direct authority.
• Comfortable in a fast-paced small company environment and able to adjust workload based upon changing priorities.
• Candidates must be authorized to work in the U.S.

We offer a chance to work with talented people in a collaborative environment and provide a top-notch compensation and benefits package, which includes an annual performance bonus, equity, health insurance, generous time off (including 2 annual holiday company-wide shutdowns) and much more. The expected salary range for this role is $170,000 to $210,00 per year. Actual pay will be determined based on experience, qualifications, geographic location, business needs, and other job-related factors permitted by law.

As an equal opportunity employer, Allogene is committed to a diverse workforce. Employment decisions regarding recruitment and selection will be made without discrimination based on race, color, religion, national origin, gender, age, sexual orientation, physical or mental disability, genetic information or characteristic, gender identity and expression, veteran status, or other non-job-related characteristics or other prohibited grounds specified in applicable federal, state and local laws. We also embrace differences in experience and background, and welcome diversity of opinions and thought, designed to create a stronger and better Allogene that is focused on developing life-changing products for patients.

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