Senior Scientist Mass Spectroscopy 2305-5830

This is a clinical-stage biotechnology company that places special emphasis on high-mortality cancers.

Territory: New Jersey/New York
Therapeutic Area: Oncology

The Senior Scientist supports the pipeline by applying LC-MS to characterize and quantitate drug candidates.

For this position, hands-on experience with HPLC and LC-MS are required and any familiarity with Agilent Q-TOF mass spectrometry instruments and metabolite identification is preferred.

Must have a clear understanding of in vivo preclinical and clinical ADME studies, the clearance route mechanism, and the role of metabolism/catabolism.

Essential Duties and Responsibilities

• Develop bioanalytical methods for research and development compounds.
• Identification and structural elucidation of non-radiolabeled in vitro and in vivo metabolites/catabolites of peptide drug candidates.
• Structural characterization of peptide impurities/degradants in bulk active and early formulation development.
• Designing and executing proteomic experiments as well as developing LC-MS based proteomics methods.
• Serve as bioanalytical representative on cross-functional project teams.
• Work independently, design experiments and report data in written reports and team presentations as required.
• Maintain accurate records of the study data.

Qualifications (Education & Experience)

• PhD, MS, or BS in Organic/Analytical/Natural Products/Protein Chemistry with 3+ (PhD), 9+ years (MS) or 11+ years (BS) of pharmaceutical industry experience.
• Hands-on experience in common sample preparation techniques (LLE, SPE, affinity capture, enzymatic digestion, homogenization etc.) in bioanalysis.
• Experience in immunocapture and protein/peptide analysis by LC-MS is a plus.
• Experience in hydrogen-deuterium exchange mass-spectrometry (HDX-MS) is a plus
• Ability to analyze data and maintain detailed and comprehensible study documentation
• Passion for science with critical-thinking and problem-solving skills.
• Strong capabilities in experimental design, execution, data interpretation and troubleshooting.
• Work productively in cross-functional teams and achieve program goals.