Senior Clinical Data Science Program Lead

AbbVie Inc.; North Chicago (IL); On-site; USD 140,000 - 190,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

401(k)

Job summary

AbbVie Data Science leads the execution of programs across clinical trials by integrating people, process, and technology to deliver business value. The role coordinates DSS study teams and cross-functional partners to meet program objectives and timelines.

You will oversee governance, analytics, and risk management while ensuring compliance with GCP/ICH and AbbVie SOPs, mentoring staff, and supporting continuous process improvements within the data science function.

Qualifications

• Bachelor’s degree in business, MIS, CS, life sciences or equivalent. Master’s preferred.
• Must have 8+ years pharma/clinical research/data management/health care experience or 10+ years project management experience.
• Understanding of clinical trial processes and stakeholders; lead role in trials.

Responsibilities

• Aligns DSS study teams with program- and study-level strategies.
• Acts as single point of contact and operational lead from DSS for assigned programs.
• Interacts with management and cross-functional teams to achieve program objectives.
• Uses operational analytics and PM tools to optimize execution and track study progress.
• Ensures adherence to GCP, ICH, AbbVie SOPs and regulatory standards.

Skills

Project leadership

Cross-functional collaboration

Regulatory awareness

Analytical skills

Communication skills

Education

Bachelor’s degree in life sciences or related field

Master’s degree preferred

Job description

AbbVie Data Science leads the execution of programs across clinical trials by integrating people, process, and technology to deliver business value. The role coordinates DSS study teams and cross-functional partners to meet program objectives and timelines.

You will oversee governance, analytics, and risk management while ensuring compliance with GCP/ICH and AbbVie SOPs, mentoring staff, and supporting continuous process improvements within the data science function.