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Data Scientist

Quality | South San Francisco, CA | Full Time

Job Description

About Allogene Therapeutics, Inc:

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™) therapies for cancer. Led by a world-class management team with significant experience in cell therapy, Allogene is developing a pipeline of “off-the-shelf” CAR T cell therapy candidates with the goal of delivering readily available cell therapy on-demand, more reliably, and at greater scale to more patients. For more information, please visit, and follow @AllogeneTx on Twitter and LinkedIn.

Job Description:

Provide excellence in statistical support and data analysis to drive the application of advanced and state-of-the-art statistical principles, tools and methodologies to improve process understanding, quality and compliance of the products, efficiency and capability of the processes and profitability of the organization.


Responsibilities include, but are not limited to:

  • With general guidance provide direct technical support to Quality, Manufacturing, Development and Regulatory Affairs with hands-on analysis of process and product data.  Applies appropriate statistical methods in order to improve and maintain optimal process control and product compliance.
  • Explain and justify application of statistical method in discussions with internal and external regulatory bodies and Health Authorities.
  • Maintain and deliver just-in-time and routine training to assure staff familiarity with appropriate application of statistical methods.
  • Actively participate and support the activities of the PD Group and continue to assess and subsequently develop the statistical capabilities at the site level.
  • Process Validation and Design Transfers:
    1. Statistical analysis of process validation data for demonstrating validity and equivalence
    2. Contribute to construction and interpretation of the results of failure mode and effects analysis (FMEA), failure mode, effects, and criticality analysis (FMECA), and fault tree analysis (FTA).
    3. Identify and apply various evaluations and tests to qualify and validate the design of new products and processes to ensure their fitness for use.
    4. Design studies using potentially critical inputs to elucidate critically of input and predict with confidence output response. Select the best designed experiment and evaluate the results through ANOVA, PLS, PLA or other relevant model.  Use these modeling and simulations techniques to support definition of process control strategy.
    5. Support process transfer process by providing study design and acceptance criteria that demonstrate comparability of transferred process and product quality.
  • Process and Product Monitoring and Controls
    1. Select, construct, apply, and interpret tools such as 1) flowcharts, 2) Pareto charts, 3) cause and effect diagrams, 4) control charts, 5) check sheets, 6) scatter diagrams, and 7) histograms
    2. Define, describe, calculate, and use process capability studies, including identifying characteristics, specifications, and tolerances, developing sampling plans for such studies, establishing statistical control, etc.   Distinguish between natural process limits and specification limits, and calculate percent defective.
    3. Define, describe, and apply the concepts of producer and consumer risk and related terms, including operating characteristic (OC) curves, acceptable quality limit (AQL), lot tolerance percent defective (LTPD)
    4. Support the compilation of Annual Product Review (APR)/Product Quality Reviews (PQRs)
  • Critical root cause investigations and data-driven decision making:
    1. Support the analysis of complex data sets to facilitate Root Cause Investigations
    2. Define, describe, and assess the efficiency and bias of estimators. Calculate and interpret standard error, tolerance intervals, and confidence intervals.   Apply and interpret the concepts of significance level, power, type I and type II errors. Define and distinguish between statistical and practical significance

Position Requirements & Experience:

  • BSc. In Statistics, Mathematics, Data Science, Natural Science or Engineering.
  • Desirable MSc. Or PhD, or equivalent experience.
  • Fluent in English language
  • Minimum 1 year experience in manufacturing. Proven process understanding of (Medical Device, Pharma, GMP, Regulatory aspects)
  • Proven experience of applied statistics is a must, e.g. in the field of DoEs and multivariate data analysis.  
  • Experience in the following software is a plus: SAS, R, Minitab, SIMCA-P+, Modde, JMP, SPSS.
  • Working knowledge of applying statistical tools, processes and programs
  • Familiarity with pharmaceutical/biotech processes
  • Familiarity with documentation in a highly regulated environment
  • Ability to work on specialized statistical software such as SAS, R, JMP, Minitab as appropriate.
  • Ability to analyze and apply GLPs and GMPs to improve the quality of the system.
  • Ability to apply industrial engineering and process improvement to production.
  • Able to develop solutions to routine technical problems of limited scope.
  • Demonstrated skills in the following areas:
    1. Problem solving and applied engineering.
    2. Basic technical report writing
    3. Verbal communication
    4. Ability to handle multiple projects at one time


As an equal opportunity employer, Allogene Inc. 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. In order to ensure reasonable accommodation for individuals protected by Section 503 of the Rehabilitation Act of 1973, the Vietnam Era Veterans' Readjustment Act of 1974, and Title I of the Americans with Disabilities Act of 1990, applicants who require accommodation in the job application process may contact the careers email at for assistance.


For more information about equal employment opportunity protections, please view the ‘EEO is the Law’ poster.