Senior Research Consultant, Evidence Review and Software (Remote - Canada)

Candidates must currently have authorization to work in the U.S. or Canada without employer sponsorship, as we are not able to provide H-1B sponsorship now or in the future for this position.

We are looking for 7+ years in HEOR, epidemiology, or pharmacoepidemiology with hands-on systematic review experience. Must have experience interpreting or reviewing statistical outputs from meta-analysis or network meta-analysis software (e.g., R packages, WinBUGS/JAGS, or equivalent). 

The Senior Research Consultant, Evidence Review and Software serves as a key subject matter expert supporting both product development and customer success for Cytel’s AI-powered systematic, targeted literature review, and evidence synthesis (meta-analysis and network meta-analysis) solutions. This role blends deep HEOR and evidence synthesis expertise with strategic customer engagement, operational delivery, and cross-functional collaboration.

• Design screening and extraction templates: Define reusable inclusion/exclusion criteria and extraction variable schemas for common HEOR review types
• Craft and adjudicate gold sets: Build annotated benchmark datasets; serve as tie-breaker on edge cases including outcome harmonization and comparability decisions relevant to quantitative synthesis
• Validate and calibrate AI outputs: Partner with data science to benchmark accuracy, surface error patterns, and adjudicate low-confidence cases 
• Refine prompts: Improve AI instructions to capture HEOR terminology, decision logic, and edge cases
• Oversee review quality: Spot-check outputs; ensure deliverables meet publication and submission standards
• Lead client engagements: Primary HEOR expert for onboarding, scoping, and deliverable review
• Own QA protocols: Define decision rules, quality standards, and production workflows; track defect rate and turnaround benchmarks
• Feedback loop to product: Translate client needs into actionable improvements; support new feature development  suitable for evidence synthesis and quantitative analysis workflows

Candidates must currently have authorization to work in the U.S. or Canada without employer sponsorship, as we are not able to provide H-1B sponsorship now or in the future for this position.

Education: Master's or PhD in Health Economics, Epidemiology, Pharmacoepidemiology, Public Health, or a related life science

Experience: 

• 7+ years in HEOR, epidemiology, or pharmacoepidemiology with hands-on systematic review experience
• Deep familiarity with PRISMA guidelines and HTA submission standards (NICE, CADTH, ICER, or equivalents)
• Strong annotation instincts and a high-quality bar for evidence synthesis including outcome definition, data consistency, and comparability for quantitative analyses
• Experience interpreting or reviewing statistical outputs from meta-analysis or network meta-analysis software (e.g., R packages, WinBUGS/JAGS, or equivalent)
• Oncology and/or real-world evidence (RWE) background
• Clear, actionable written communication suited for both technical and non-technical audiences 
• Client-facing experience: Comfortable presenting to stakeholders, managing expectations, and delivering under deadlines
• Self-directed with the ability to balance strategic input and hands-on execution
• Comfort working with sensitive client data; follow our QA and privacy SOPs
• Experience guiding or evaluating ML/NLP tools for text classification or extraction
• Comfort reviewing structured outputs (Excel, CSV) and spotting data quality issues
• Prior consulting or CRO experience with external client delivery
• Experience building or scaling operational workflows for evidence synthesis teams
   

Skills:

• Excellent written and oral communication skills, both formal and informal 

• Strong analytical skills including interpretation of quantitative evidence synthesis results

• Excellent people skills to interact with staff, colleagues and cross-functional teams, and third parties.

• High comfort level with a broad scope of software development technology