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

American Society of Anesthesiologists®•Schaumburg, DC

12d•$115,000 - $145,000•Hybrid

About The Position

The Systematic Review Scientist will lead and support high-quality evidence synthesis projects, with a strong emphasis on meta-analyses and network meta-analyses. This role requires deep methodological expertise combined with a forward‑looking mindset. The successful candidate will be comfortable leveraging artificial intelligence (AI) and automation tools to increase efficiency, consistency, and scalability across the evidence synthesis lifecycle.

Requirements

Bachelor’s degree in related field required.
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.
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.

Nice To Haves

Master’s degree in Public Health, Epidemiology, Statistics, Health Economics, or related discipline preferred.
Published peer-reviewed systematic reviews and/or network meta-analysis is preferred.
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.
Ability to design efficient, scalable workflows that integrate AI while preserving methodological rigor and transparency is preferred.

Responsibilities

Design, conduct, and report systematic reviews in accordance with methodological best practices (e.g., PRISMA, Cochrane, GRADE).
Perform pairwise meta-analyses 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.
Ability to perform work in alignment with ASA core values: Dedication, Collaboration, Commitment to Excellence, Continuous Improvement.