Systematic Review Scientist - Schaumburg, IL; Washington, DC; or Remote

About the role

The American Society of Anesthesiologists (ASA) is seeking a Systematic Review Scientist to join our collaborative team. We provide education, resources, and advocacy to enhance patient care. This role requires a strong background in evidence synthesis, with a focus on meta-analyses and network meta-analyses.

Responsibilities

• Design, conduct, and report systematic reviews in compliance with methodological best practices.
• Perform pairwise and network meta-analyses, including model selection, assessment of heterogeneity, inconsistency, and sensitivity analyses.
• Develop and execute reproducible workflows for literature searching, screening, data extraction, and risk-of-bias assessment.
• Lead or contribute to protocol development, statistical analysis plans, and final reports/manuscripts.
• Collaborate with clinical experts, statisticians, and stakeholders to ensure methodological rigor and relevance.
• Apply AI-enabled tools (e.g., machine-learning-assisted screening, data extraction, LLM-based summarization) to streamline review processes while maintaining quality and transparency.
• Evaluate, validate, and refine AI workflows to ensure appropriate use, auditability, and methodological integrity.
• Stay current with advances in evidence synthesis methods, statistical approaches, and AI applications.
• Mentor less experienced staff and contribute to internal methodological standards and guidance, as appropriate.
• Provide support, project management, subject-matter expertise, and liaison services to assigned Committees and/or Councils.

Qualifications

• Bachelor’s degree in related field required. Master’s degree in Public Health, Epidemiology, Statistics, Health Economics, or related discipline preferred.
• Minimum 5 years of experience with health care research.
• Demonstrated experience conducting systematic reviews and meta-analyses, including hands-on experience with network meta-analysis.
• Published peer-reviewed systematic reviews and/or network meta-analysis is preferred.
• Strong understanding of evidence synthesis standards, risk-of-bias tools, and reporting guidelines.
• Experienced user of Microsoft Office products: Word, Excel, and PowerPoint.
• Proficiency with statistical software used for meta-analysis (i.e., R, Stata, SAS, or equivalent).
• Experience using reference management and systematic review platforms (i.e., EndNote, Covidence, DistillerSR, Rayyan, or similar).
• Familiarity with reproducible research practices (i.e., version control, reproducible code) is preferred.
• Experience working with guideline development, HTA, or regulatory contexts is preferred.
• Practical experience using AI or machine-learning-enabled tools to support systematic review tasks (i.e., screening, data extraction, summarization, quality checks) is preferred.
• Able to design efficient, scalable workflows that integrate AI while preserving methodological rigor and transparency is preferred.

Benefits

ASA offers a comprehensive benefits package including medical, dental, and vision insurance, a 401K match, a free fitness center, breastmilk shipping, CALM subscription, volunteer committees, employee resource groups, and more. Detailed information can be found at: https://www.asahq.org/about-asa/work-at-asa/benefits.

Compensation

This position is an exempt/salaried position. The target hiring pay range for this position is: $115,000 to $145,000 annually. This position is not eligible for a yearly bonus/incentive. Compensation decisions consider a wide range of factors, including but not limited to relevant experience, skills, certifications, business needs, and organizational policies. ASA strives to be transparent with its pay practices both internally and externally.

Equal Opportunity Employer

ASA is an Equal Opportunity Employer of Minorities, Females, Individuals with Disabilities, and Veterans. Decisions affecting employment are considered without regard to disability, race, color, religion, gender, national origin, age, genetic information, military or veteran status, sexual orientation, marital status, or any other protected characteristic.