(Apply in 3 Minutes) Analyst [GC-MS Data Interpretation Chemist]
TÜV SÜDBengaluru, Karnataka, India
18 hours ago
Job description
Key Responsibilities :
Interpret GC-MS data (primarily EI) for identification of unknowns using spectral deconvolution and comparison to library databases for chemical characterization studies.
Evaluate spectral quality, match scores, and fragmentation patterns using a weight-of-evidence approach, including critical assessment of database matches.
Apply knowledge of retention indices and chromatographic behavior to confirm compound identity.
Collaborate with technical analysts, chemists, and project managers to communicate findings, resolve discrepancies, and meet client expectations.
Ensure data integrity and compliance with regulatory and accreditation standards (e.g., ISO 10993, ISO 17025, GLP).
Document findings in established systems, supporting traceability and reporting.
Contribute to method development and optimization by providing feedback on spectral data trends and anomalies.
Support improvement of SOPs, templates, and data analysis workflows.
Identify and troubleshoot potential prep or instrument-related issues affecting data integrity.
Participate in continuous improvement initiatives and inter-laboratory collaborations.
Other duties as assigned by management.
Additional Knowledge / Qualifications :
BS / B.Sc in Chemistry or a related field with 5+ years relevant experience, or MSc. / PhD with 2+ years of relevant experience.
Proficient in interpreting GC-MS and chromatographic data.
Experience working in a regulated environment (ISO 17025, ISO 10993, GLP / GMP).
Familiarity with Microsoft Excel for data documentation and review.
Preferred Candidate :
Background in organic chemistry, including fragmentation patterns under EI / CI, volatility, retention index behavior.
Experience with extractables & leachables, particularly in a medical device or pharmaceutical context.
Understanding of instrumental analysis workflows and solution preparation.
Awareness of how sample prep or instrument anomalies affect data outcomes.
Familiarity with relevant databases and software for compound identification.