Principal Statistician, Advanced Analytics
BresMed, United Kingdom
Job Description
Are you interested in working for a truly employee focussed company with exceptional work life balance, in a cutting-edge industry, where you can develop globally valued skills and apply your knowledge to improving healthcare?
About BresMed
BresMed is a health economic and outcomes research (HEOR) consultancy that works with pharmaceutical companies and medical device manufacturers, helping them demonstrate the clinical and economic value of their products to governments and other healthcare payers and providers.
Everything we do is grounded in our three company principles: Fulfilled Team, Delighted Clients and Thriving Business.
Why BresMed?
Over that past 15 years we’ve grown to employ over 160 people in the UK, India, Ireland, the Netherlands and the US. As we’ve grown, our commitment to scientific rigor, innovation, employee wellbeing and client success has been unrelenting. Our office dynamic is intellectually stimulating and focused on delivering excellence within a vibrant culture where everybody matters.
We firmly believe that we all have a valuable contribution to make and closely support each other to build a career that suits our skills and personal interests. Many of us joined as graduates and have grown into senior roles
Does this sound like your ideal work environment? Read on
Your role:
This opportunity is to join a newly formed team, Advanced Analytics, which sits within the Modelling and Analytics practice area, alongside the Health Economic and Statistics Teams. We are seeking an experienced Bayesian statistician with the enthusiasm, vision and flexibility in approach required to play a key and influential role within the Advanced Analytics team. The right candidate will enjoy investigating new methods, supporting and coaching other statisticians and health economists, and be able/willing to contribute to the growth and evolution of the Advanced Analytics team internally and externally.
Key responsibilities will include, but not be limited to:
- Learning and applying new methodologies and techniques in the evolving field of health technology assessment and reimbursement. The development and application of Bayesian methods for the synthesis of diverse data sources will be a major focus for this role
- Implementation of emerging methods in terms of documents, internal training and R code. Experience with intermediate/advanced concepts in R programming such as building packages, version control and the use of Shiny would be beneficial.
- leading statistical input and providing expert guidance to projects, developing statistical analysis plans, performing and reporting statistical analysis as standalone research or for input into health economic models that will provide direct information to clients, and governing/reimbursement bodies and/or for publication.
- Close collaboration, particularly with the Statistics and Health Economics teams within the modelling and analytics practice area and also cross-functionally with the Evidence Evaluation and Value Demonstration practices, is an essential part of the role. Furthermore, this role is client-facing, and you will be required to contribute directly to business development via input into proposals to clients.
The role can be tailored to an individual candidate’s strengths and aspirations, but will include a mix of roles and responsibilities, including strategic input and oversight of statistical content on both client and internal research and development projects, collaboration internally and externally with experts in specific fields, programming, writing (planning, reporting, manuscripts and submission documents), quality control, mentoring, training, and for the suitable candidate, there will be line management opportunities.
Requirements
Your Skills:
We are looking for enthusiasm, vision, flexibility in approach and the desire to grow into a key and influential role within our Advanced Analytics team. You will ideally have:
- A postgraduate qualification (MSc, PhD) in a statistical/mathematical topic
- Excellent numerical and critical thinking ability
- Experience with Bayesian methods and techniques such as MCMC implemented using software such as JAGS, OpenBUGS or Stan including the capability to implement novel models and adapt existing models. For example, experience with one or more of the following would be an advantage:
- · Synthesis of clinical trial data with external data such as previous trials, general population mortality or observational data as prior information to inform long term extrapolation of outcomes · Incorporation of expert opinion to inform estimation and extrapolation of clinical outcomes · Joint synthesis of related endpoints and application to s