Senior Analyst, Data Quality (Preclinical Imaging)

Location: hirify.global office in Needham, Massachusetts, United States

Annual base salary: $75,000–$90,000

Company

hirify.global develops and supports pre-clinical imaging and data solutions for pharmaceutical and scientific research programs.

What you will do

• Lead and support the QC Analyst team, resolve complex scientific data integrity issues, and mentor junior colleagues.
• Review raw, pre-processed, and analyzed pre-clinical data across modalities and therapeutic areas for accuracy, consistency, and completeness.
• Collaborate with Project Management, Image Analysis, Lab, and Study Director teams to meet project quality and timeline requirements.
• Review reporting for consistent data presentation across studies, sponsor programs, and alliance agreements.
• Identify QC bottlenecks and work with Analysis and Software teams to streamline and automate manual workflows.
• Contribute to SOPs, templates, and internal quality control guidelines.

Requirements

• Master’s degree with several years of experience in imaging or pharmaceutical project management, or a relevant bachelor’s degree with 5+ years of equivalent experience.
• Experience leading and mentoring colleagues, including line management and leadership responsibilities.
• Knowledge of nuclear medicine modalities and documentation related to animal handling, radiochemical procedures, and study design.
• Experience with pre-clinical in vivo imaging applications such as MRI, PET, SPECT, or CT, including data acquisition, analysis techniques, and quality control.
• Strong analytical, organizational, communication, troubleshooting, and prioritization skills.
• Fluent English required.

Culture & Benefits

• Medical, dental, and vision benefits for employees and families, including Flexible Spending Accounts.
• Paid time off, holidays, and sick time.
• Internal growth, development programs, and training.
• 401(k), life and accident insurance, and disability insurance.
• Collaborative, cross-functional work with opportunities to improve data quality and operational efficiency.