Consultant, Advanced Analytics: Meta-Analysis (HTA Statistician)

Job Title: Consultant, Advanced Analytics: Meta-Analysis (HTA Statistician)

Job Location: Uxbridge, UK

Job Location Type: Remote

Job Contract Type: Full-time

Job Seniority Level: Mid-Senior level

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• A Master's or Doctoral-level degree in applied statistics, health economics, and related quantitative fields.
  
• A minimum of 3 years of hands‑on experience working in the pharmaceutical industry, a consultancy, Access/HTA/reimbursement agency, or academic institution (pharma affiliate experience is a plus).
  
• Demonstrate in-depth knowledge of Access and HTA, clinical research and development methods, and international payer evidence requirements.
  
• Skilled in research design and statistical methods, such as Generalized Linear Models, Survival analysis, Network Meta‑Analysis, and Bayesian statistics and are proficient in R and GitLab (experience with SAS, Python, WinBUGS, JAGS, or other relevant statistical software is a plus).
  
• Strong strategic, collaboration, and communication skills, strong organization, planning, and prioritization skills with an ability to meet tight deadlines, and strong written and verbal communication skills in English.
  

For this position, we have flexibility to hire at either Consultant or Senior Associate level.

The Consultant, Advanced Analytics: Meta-Analysis contributes statistical capabilities and methodological leadership at all stages of projects, from planning to completion. The role would work with junior team members in designing, developing, and delivering client solutions across multiple projects – leveraging competencies in statistical theory, data analysis and interpretation, regression analysis, systematic review and evidence synthesis methodologies. The individual must have a Master's or Doctoral Degree in Health Economics, Health Policy, Statistics, Biostatistics, Mathematics, or other quantitative fields. They should be proficient in data analytics and statistical software/tools like WinBugs, R, Stata, Python, and SAS.

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• Provide expert input on the design of clinical development programs to ensure Access/HTA evidence needs are considered within global development and commercialization strategies.
  
• Identify evidence gaps, possible data sources, and design and implement robust evidence-generation plans.
  
• Ensure Access/HTA evidentiary activities are strategically aligned with other functions within Global Access and the wider organization (affiliates, Product Development, commercial, etc.).
  
• Plan and conduct statistical analyses of clinical trials and other relevant data sources and develop supporting technical documentation for statistical analyses and economic models.
  
• Interpret and communicate the findings of analyses and work closely with affiliates to incorporate global statistical and health economics input into their local reimbursement applications.
  
• Lead or contribute to cross‑functional teams within a matrix structure and actively contribute to the development of methodologies and continuous improvement within the Evidence Chapter.
  
• Keep up to date with the changing Access/HTA landscape and academic research to ensure current access trends and methodologies are incorporated into evidentiary plans and build relationships with relevant external statistics, health economics, Access/HTA, and policy experts.
  

The Consultant, Advanced Analytics: Meta‑Analysis is responsible for ensuring that all assigned projects are being conducted in an efficient manner and that quality and client satisfaction is maximized at all times -- ensuring the direction of the project and the quality of the deliverables meet the project objectives and the client needs. Further, Consultants are expected to guide the Senior associates and Associates in their daily duties and to flag any areas of acute training needs to their line managers. Supported by the senior staff and Business Development partners, the Consultant is responsible for maintaining client relationships on their projects.

The successful candidate will be part of multi-disciplinary research teams and will be expected to provide statistical expertise and methodological leadership at all stages of projects from planning to completion. Duties will vary according to the nature of the projects. These may include independently contributing to the preparation of network meta‑analysis protocols, reviewing data extracted from systematic literature reviews, conducting feasibility assessments, generation of network diagrams, critical assessment of study heterogeneity, conducting network meta‑analysis, and assisting with the interpretation and dissemination of findings. The successful incumbent is expected to also support ongoing thought leadership and innovation objectives of the unit in the field of advanced analytics including, but not limited to:

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• Pairwise meta‑analysis
  
• Mixed treatment comparison
  
• Indirect treatment comparison
  
• Network meta‑analysis
  
• Match adjusted indirect treatment analysis
  
• Meta‑regression
  
• Single‑arm trial analysis
  
• Simulated treatment comparison
  
• Surrogate outcome assessment