Position Summary:
Orbital is seeking an exceptional Sr. Scientist/Engineer with deep expertise in nanoparticle process and formulation development. In this role, the individual will work closely with the Delivery, Process Development, and Analytical groups, as well as external CDMOs, to advance our early pipeline into development. The candidate will work on formulation and scale up of lipid nanoparticles (LNPs) and other non-viral delivery matrices targeting different organs and cell types for a variety of therapeutic applications.
Responsibilities:

• Lead and support the development and scale-up of lipid nanoparticle production across mixing geometries, scales, components, and payloads.
• Design and execute experiments to enable a robust and reproducible formulation process for manufacture of clinical trial materials.
• Design and execute experiments both independently and as a team to evaluate and optimize drug product stability.
• Collaborate with internal Delivery, Process Development and Analytical groups, as well as external manufacturing CDMOs.
• Provide support with tech transfer activities for manufacturing of drug product.
• Generate high quality documentation in support of regulatory filings and tech transfer.
• Communicate and present rigorous scientific findings both internally and externally.

Qualifications:

• M.S. or Ph.D. in Pharmaceutical Sciences, Chemical engineering, Bioengineering or a related field.
• 6-8 years of experience including at least 6 years of drug product CMC development is required.
• Must have a deep understanding of lipid nanoparticle formulation for RNA therapeutics.
• Prior industry experience with nanoparticle formulation and scale-up is required.
• Familiarity with ultrafiltration and aseptic unit operations for sterile drug product manufacture.
• Experience using statistical computer languages and modeling software (R, Python, SLQ, JMP, etc.) to manipulate data and draw insights from large data sets.
• Knowledge of statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) is a plus.
• Ability to adapt to increasing scope and complexity of work brought on by growth/change.