Senior Bioanalytical LC-MS & DMPK Lead

IQVIA; Cambridge; Remote; GBP 65,000 - 90,000; Full time

Benefits offered by this job

Generous pension

Bonus

Health cover

Job summary

IQVIA Cambridge is seeking an experienced bioanalyst to join our DMPK team, delivering bioanalysis and MS-based method development for small and large molecules in early discovery settings.

The role combines hands-on analytical work with project leadership, mentoring colleagues, and driving continuous improvement across drug discovery programmes.

You will collaborate across multidisciplinary teams in a matrix environment and contribute to data quality and timely decision making.

Qualifications

• BSc or equivalent in relevant scientific area.
• Industry experience in pharma/biotech or other commercial organisations.
• Bioanalytical method development for challenging analytes.
• Excellent communication skills and ability to work in a matrix environment.
• Experience mentoring junior colleagues.

Responsibilities

• Developing, optimising and executing bioanalysis for in vivo DMPK studies for small and large molecules.
• Lead scientific and technical projects, ensuring delivery of high-quality data to timelines.
• Mentor, coach and develop colleagues, acting as a technical role model.
• Drive innovation through development of novel assays and analytical approaches.
• Collaborate with multidisciplinary teams to support drug discovery programmes.

Skills

Mass Spectrometry

LC-MS/MS

Bioanalysis

Project leadership

Education

BSc or equivalent in relevant scientific area

Tools

Mass Spectrometry instrumentation

MS software

Job description

IQVIA Cambridge is seeking an experienced bioanalyst to join our DMPK team, delivering bioanalysis and MS-based method development for small and large molecules in early discovery settings.

The role combines hands-on analytical work with project leadership, mentoring colleagues, and driving continuous improvement across drug discovery programmes.

You will collaborate across multidisciplinary teams in a matrix environment and contribute to data quality and timely decision making.