Oxford PharmaGenesis has an exciting opportunity for a Lead Biostatistician to join our company to help increase our biostatistics capabilities.
You will be responsible for leading and designing statistical analyses, including meta-analyses, feasibility assessments and indirect treatment comparisons (ITCs). You will work closely with our Value Demonstration Practice, which conducts systematic literature reviews and develops resulting communications.
You will provide strategic advice on methodology, confidently liaise with clients, and promote our biostatistics capabilities to new and existing clients. You should have a proven track record of business development, building close client relationships and collaborating effectively with cross-functional teams. You will be integral to leading, motivating and training a growing team.
You should have strong project management skills, plus the ability to adapt to changing priorities and to meet tight deadlines while maintaining quality. You will need excellent communication skills to convey complex statistical information effectively to both technical and non-technical audiences.
Our Value Demonstration Practice is based in our Oxfordshire and London offices, so this role will suit someone who can work from one of our Oxford offices or our London office at least 2 days each week.
We are looking for a Lead Biostatistician who has:
- a PhD or MSc in statistics, biostatistics or a related field
- at least 8 years of experience as a statistician supporting health economics and outcomes research (HEOR) and health technology assessment (HTA) analyses, clinical trials, medical affairs or clinical development in a consultancy or industry setting (e.g. the pharmaceutical industry, biotechnology industry or in a clinical research organization)
- an understanding of HEOR and market access principles, including up-to-date knowledge of statistical methods used in meta-analyses and ITCs
- a proven track record of designing, performing and overseeing statistical analyses, ensuring their quality and integrity through rigorous review stages and their adherence to standard operating procedures, regulatory and HTA guidelines (e.g. NICE DSU)
- proficiency with statistical software (e.g. SAS, R/R-studio), plus programming experience and experience with data management and analysis
- experience in publishing results, including writing abstracts and manuscripts.