Senior Statistician

Overview / About us

Lumanity is dedicated to improving patient health by accelerating and optimizing access to medical advances. We partner with life sciences companies around the world to generate evidence to demonstrate the value of their product, translate the science and data into compelling product narratives, and enable commercial decisions that position these products for success in the market. We do this through strategic and complimentary areas of focus:
Asset Optimization and Commercialization, Value Access and Outcomes, Medical Strategy and Communications, and Real‑World Evidence.

We are seeking a seasoned Statistician with a background in Health Economics and Outcomes Research (HEOR)/Health Technology Assessment (HTA) to join our HEOR Research team. In this senior level role, the statistician will play a key and influential role and contribute to the growth and evolution of the team.

Key responsibilities will include, but are not limited to: 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. Common types of analyses/projects performed include, but are not restricted to:

• Survival analyses:
  • Parametric survival analyses
  • Adjustments from treatment switch/cross‑over within clinical trials
• Indirect treatment comparisons:
  • Network meta‑analyses
  • Population‑adjusted indirect comparisons (e.g. matching‑adjusted indirect comparisons)
  • Time‑varying indirect treatment comparisons (e.g. fractional polynomials)
• Analyses of clinical trial data (e.g. quality of life)
• Analyses of observational data / real world evidence
• Statistical input into reimbursement submissions to health technology agencies

The successful candidate should be motivated to learn and apply new methodologies and techniques in the evolving field of HTA and reimbursement.

Close collaboration, both within the Statistics team, wider Research team and cross–functionally with the HEOR Consulting team, is an essential part of the role. Furthermore, this role is external‑facing, and you will be required to demonstrate professional excellence in client and other external stakeholder interactions.

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 projects, collaboration internally and externally with experts in specific fields, programming, writing (planning, reporting, manuscripts and submission documents), quality control, mentoring, training, line management, and for the suitable candidate, there are research and development opportunities.

This opportunity offers flexible work setting options to suit individual needs. This can be fully remote with options to work in any of our offices as needed, if preferred.

The ideal candidate is an enthusiastic statistician that enjoys investigating new methods, supporting and coaching other statisticians and health economists, and has the vision and flexibility approach required to contribute to the growth and evolution of the business.

• A postgraduate qualification (MSc, PhD) in a statistical/mathematical topic
• Multiple years of professional experience in planning, performing and reporting statistical analyses within a HEOR consultancy, HTA agency, biostatistics or contract research organization (CRO) environment
• Experience with Bayesian methods and techniques such as MCMC or HMC implemented using software such as JAGS, OpenBUGS or Stan including the capability to adapt existing models is essential.

Experience in health research with one or more of the following:

• Use of hierarchical models for statistical modelling and data synthesis
• Population‑adjustment methods and/or time‑varying network‑meta‑analysis methods for evidence synthesis
• Extrapolation of long‑term survival outcomes, including flexible methods (e.g. parametric survival methods incorporating…