MSAT Data Science Engineer

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:

Allogene’s Manufacturing organization is building a world class team that is focused on delivering potentially lifesaving therapies to patients. We are seeking a highly motivated individual to join us as a Data Science Engineer, Manufacturing Sciences and Technology. This role will have hands-on responsibility over all manufacturing process data, including ensuring robust data infrastructure, data collection and analysis, and establishing best data management practices. This role will directly support technical and strategic initiatives to advance process understanding, control and qualification activities from late-stage development through launch/commercialization. The position is based at Allogene’s manufacturing facility in Newark, CA.

Responsibilities include, but are not limited to:

· Ownership of data lake infrastructure, including data ingestion, cleaning, organization, visualization and integration with data analysis tools.

· Translate process understanding into data and develop data analysis methodology to inform process and quality decisions.

· Generate data packages to support PPQ-readiness, PPQ execution and BLA submission for allogeneic CAR-T therapies and critical starting materials

· Able to apply and develop advanced technologies, scientific principles, theories and concepts to meet the needs of the Process Development and Manufacturing teams, including support of technology transfers

· In-depth knowledge of GMP and regulatory expectations and experience with regulatory inspections

· Work with Quality, Facilities & Engineering, Process Development and IT to ensure cross-functional alignment

· Closely partner with the Process Development and Quality groups to ensure continuity of data, robust process design and monitoring of product quality

· Contribute to company-wide AI initiatives as a thought leader for introduction and implementation of new AI tools for continuous improvement and innovation.

· Engage with broader manufacturing team to enable accomplishment of department goals

· Other duties as assigned

Position Requirements & Experience:

· Bachelor’s degree in science or engineering (with a focus on computer science or data science preferred) with a minimum of 6 years of experience within a GMP pharmaceutical manufacturing space and 2 years of direct data science experience within a GMP pharmaceutical manufacturing space.

· Late-stage clinical and commercial experience preferred.

· Proficiency in programming languages including SQL, Python and R and data analytics tools, including JMP, Spotfire, Tableau, R-Studio

· Knowledge of pharmaceutical manufacturing processes and GMP requirements for data integrity. Cell therapy experience preferred.

· Experience developing and implementing data solutions with machine learning and AI preferred.

· Excellent written and verbal communication skills

· Excellent organizational skills and an ability to prioritize effectively to deliver results within established timelines

· Ability to work independently and as part of a team

· Ability to travel up to 10%

· 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 $120,000 to $140,00 per year. Actual pay will be determined based on experience, qualifications, geographic location, business needs, and other job-related factors permitted by law.