Senior /Principal Scientist, Protein Science
On-siteCambridge, Massachusetts, United States
Job Summary
Define and lead analytical and biophysical characterization strategies to support therapeutic protein discovery, lead optimization, and development candidate selection. Design, execute, and interpret studies including mass spectrometry, stability, and developability assessments to characterize molecular identity, quality attributes, and degradation pathways. Integrate orthogonal datasets to establish structure-property relationships and translate findings into protein engineering and selection decisions. Serve as the characterization lead on cross-functional teams with Biologics Discovery, Biology, CMC, and external CROs to define workflows and solve complex scientific challenges. Evaluate and implement new technologies to strengthen internal capabilities and mentor scientists within the Protein Science organization.
Required Qualifications
- Ph.D. in Biochemistry, Biophysics, Protein Chemistry, Chemical Engineering, or a related scientific discipline
- 3+/5+ years of relevant industry and/or postdoctoral experience
- M.S. with 8+/10+ years of relevant industry experience in therapeutic protein discovery, characterization, or early development
- B.S. with 12+/15+ years of relevant industry experience in therapeutic protein discovery, characterization, or early development
- Deep understanding of protein chemistry, molecular biophysics, therapeutic protein quality attributes, and the analytical and biophysical principles governing protein stability, heterogeneity, and developability
- Demonstrated experience designing, executing, and interpreting analytical, biophysical, developability, and stability characterization studies to support therapeutic protein discovery, lead optimization, and development candidate selection
- Extensive hands-on experience with analytical characterization techniques, including SECHPLC/UHPLC, IEX/CEX, HIC, CE-SDS, icIEF, AC-SINS, and LC-MS (e.g., intact mass, peptide mapping, PTM characterization)
- Extensive hands-on experience with biophysical characterization techniques including DLS, DSF/nanoDSF, DSC, and related methodologies
- Experience designing and interpreting developability studies, including the use of orthogonal approaches such as PEG solubility, AC-SINS, self-interaction, viscosity, solubility, and polyspecificity/nonspecific binding assays
- Experience designing and interpreting accelerated stability, stress, and forced degradation studies, including the investigation of degradation pathways, molecular liabilities, and critical quality attributes
- Demonstrated ability to integrate analytical, biophysical, and biological datasets to establish structure-property relationships and translate findings into protein engineering, candidate selection, and development decisions
- Proven ability to lead scientific initiatives and collaborate effectively across multidisciplinary teams
- Excellent scientific communication, critical thinking, and problem-solving skills, with the ability to communicate complex scientific concepts and influence technical decision-making
Desired Qualifications
- Experience with advanced protein-protein interaction techniques, including SPR, BLI, KinExA, or related technologies
- Experience with therapeutic protein expression, purification, and process development
- Experience with complex biologic modalities (e.g., multispecific antibodies, antibody-drug conjugates, fusion proteins, or other engineered biologics)
- Experience working at the interface of experimental and computational sciences, supporting AI/ML-enabled protein engineering and therapeutic discovery through the generation of high-quality analytical and biophysical datasets
- Experience implementing new analytical technologies, establishing laboratory capabilities, and developing scalable scientific workflows
- Experience working with large, multidimensional datasets and leveraging modern computational and AI-enabled tools (e.g., Python, workflow automation, AI coding assistants, interactive scientific applications, and data visualization platforms) to improve scientific productivity, data analysis, and decision-making
- Experience managing external CROs and scientific collaborations
- Experience mentoring scientists and contributing to the growth of a collaborative scientific organization
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