via Indeed · 16 September 2026 ·3 days ago

Associate Consultant - Evidence Review

Lumanity
London Internship
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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 complementary areas of focus: Asset Optimization and Commercialization, Value Access and Outcomes, Medical Strategy and Communications, and Real\-World Evidence.
Responsibilities / Position overview:

The Associate Consultant will apply their research training to real\-world evidence questions that shape how treatments reach patients, working across therapeutic areas for pharmaceutical and healthcare clients. The role sits within Lumanity's Evidence Review \& Statistics team, where you will design and implement literature reviews that will feed into regulatory submissions, HTA dossiers, publications, client strategy and evidence\-based decisions.

In this role, you will contribute to the design, delivery, and interpretation of evidence review projects, with increasing responsibility for managing defined workstreams and producing high\-quality outputs. You will assess the relevance and quality of evidence, identify evidence gaps and methodological issues, and support the development of clear, well\-reasoned conclusions and recommendations for clients.

Responsibilities

  • Deliver a range of evidence reviews, including SLRs, TLRs, reviews supporting economic models and indirect treatment comparisons, and strategic evidence decks

  • Learn and apply industry methodological guidelines and keep pace with evolving standards in evidence synthesis

  • Apply critical thinking to assess the quality and relevance of evidence, and translate findings into clear, well\-reasoned conclusions that address the underlying research and client question

  • Synthesize findings across studies and evidence sources, identifying patterns, inconsistencies, limitations, and evidence gaps rather than reporting results in isolation

  • Contribute to client\-facing deliverables, regulatory submissions, HTA dossiers, and academic publications, including development of clear, concise, and logically structured written content

  • Take ownership of your workload across multiple projects, maintaining rigour and meeting deadlines, prioritising effectively when timelines or project needs change

  • Build working knowledge across therapeutic areas and apply it to new projects

  • Develop, validate, and apply Lumanity agentic AI innovations and other AI software to evidence review workflows, while applying appropriate scientific judgement and quality\-control processes to AI\-assisted outputs
Qualifications:
  • PhD (preferred) in epidemiology, pharmaceutical sciences, biostatistics, public health, or a related health sciences discipline. Candidates with a Master's degree are welcome to apply. Preference given to candidates with internship or placement year at CRO or pharmaceutical company

  • Familiarity with systematic literature review methods. Practical experience contributing to evidence reviews, including screening, data extraction, quality assessment, evidence synthesis, or report development, is desirable.

  • Experience with indirect treatment comparisons (e.g. Bucher, NMA, MAIC, STC), ITC feasibility assessments, or health technology assessment (HTA) submissions is a plus
*Please note: This role may require occasional travel, for example to attend client meetings in person or for conference attendance.* *Lumanity is an equal opportunities employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.*
Benefits:
  • Competitive salary

  • Bonus

  • Pension

  • Private Healthcare

  • Dental Cover

  • Enhanced Eye Care Cover

  • Electric Car Scheme

  • Staggered working hours

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