Statistician
دوام كامل
في Skyward Analytics
في
India
نُشرت يوم January 30, 2025
تفاصيل الوظيفة
About Us We are a boutique data analytics consultancy specialising in the domain of Health Economics and Outcomes Research (HEOR), pricing, and market access. We provide services to pharmaceutical and medical device companies as well as support midsize and large consultancies globally. Our in-house team of expert health economists and systematic reviewers deliver high-quality work within the stipulated timelines. Key responsibilities:
- Conduct statistical analysis commonly required for submissions to HTA agencies such as NICE and PBAC.
- Develop proposals for clients, project reports and other deliverables.
- Design, analyse, and interpret data using a wide range of statistical approaches and applicable software.
- Review study plans, including randomization, sample size, and analysis, as well as reports for internal or external studies (e.g., statistical review of SPRs, technical reports, presentations) according to Skyward best practices.
- Identify and develop methodologies, strategies, findings in reports and slide decks.
- Develop and execute statistical analysis plans (SAP) for clinical trial data using R or SAS.
- Digitize and conduct parametric survival analysis using Kaplan-Meier data publications as well as from the clinical trials.
- Conduct indirect treatment comparisons and Network Meta-Analyses (NMA).
- Provide support to the health economic modelling team regarding queries.
- Provide writing support for publications based on statistical analyses.
- Communicate verbally as well as in writing – detailed technical report of the analysis performed.
- Maintain effective communication with clients and the internal project team to ensure smooth and timely project execution.
- 4+ years of experience in Health Economics and Outcomes Research (HEOR)
- Education: MS or PhD in Statistics or relevant fields
- Must have experience with health technology assessment (HTA) submissions
- Advanced programming skills in R is required.
- Good knowledge and good understanding of key statistical concepts and techniques
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