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Data Scientist – Decision Science & Modelling

Job in Greater London, London, Greater London, W1B, England, UK
Listing for: QQFS (Qualitative & Quantitative Fieldwork Services)
Full Time position
Listed on 2026-07-26
Job specializations:
  • IT/Tech
    Data Scientist
Salary/Wage Range or Industry Benchmark: 70000 - 110000 GBP Yearly GBP 70000.00 110000.00 YEAR
Job Description & How to Apply Below
Location: Greater London

Company Description

A Japanese global leader in the provision of ground-breaking and innovative technological and research solutions to the healthcare industry. The M3 Group operates in the US, Asia, and Europe with over 5.8 million physician members globally via its physician websites which include , , , , , and medlive.cn. M3 Inc. is a publicly traded company on the Tokyo Stock Exchange (jp:2413, NIKKEI 225) with subsidiaries in major markets including the US, UK, Japan, South Korea, and China, and in 2020 was ranked in Forbes’ Global 2000 list.

The M3 Group provides services to healthcare and the life science industry. In addition to market research, these services include medical education, ethical drug promotion, clinical development, job recruitment, and clinic appointment services. M3 has offices in Japan, UK, France, Germany, Brazil, Sweden, China, USA, and South Korea, as well as India.

Due to continued growth, M3 MR is seeking aData Scientist – Decision Science & Modelling in London, UK.

Business Unit Mission

M3 MR, part of M3 Inc., provides the most comprehensive and highest-quality healthcare market research recruitment, data collection, and insight support services globally. With proprietary access to healthcare professionals and patient communities across more than 70 countries, M3 MR partners with pharmaceutical, biotech, medical device, and market research agencies to deliver trusted, compliant, and decision-ready insights at speed and scale.

M3 MR holds ISO 20252, ISO 27001, and ISO 27701 certifications, reflecting the group’s commitment to data quality, respondent integrity, information security, and operational excellence across quantitative and qualitative methodologies. The group combines deep healthcare expertise, advanced technology platforms, and global operational reach to support clients across the full research lifecycle.

Job Description

We are seeking a Data Scientist to design and deliver analytical models and decision-support systems that improve understanding, prediction and decision‑making across the business.

The role focuses on building practical models of complex real‑world systems, working with imperfect data, uncertainty and competing objectives to generate commercially valuable outcomes.

Responsible for developing deployable analytical solutions in partnership with Engineering teams, while not owning production infrastructure or application development.

Key Responsibilities Model Development
  • Design, develop and maintain statistical, probabilistic and simulation‑based models.
  • Translate complex business questions into tractable modelling problems.
  • Select appropriate modelling approaches based on the characteristics of the problem rather than methodological preference.
  • Develop prototypes and working solutions iteratively, refining approaches as new information becomes available.
  • Build analytical assets that can be reused as products, decision‑support tools or operational capabilities.
  • Design and analyse experiments to evaluate interventions, operational changes and model effectiveness.
Inference & Uncertainty
  • Work effectively with incomplete, imperfect and evolving datasets.
  • Develop approaches for estimating missing information and combining evidence from multiple sources.
  • Quantify uncertainty and communicate appropriate confidence in model outputs.
  • Test assumptions and identify limitations within modelling approaches.
Optimisation & Decision Support
  • Develop frameworks that improve operational and commercial decision‑making.
  • Evaluate alternative actions, trade‑offs and potential outcomes.
  • Support automation of appropriate decision processes through analytical models.
  • Design experiments and simulations that inform strategic and operational choices.
Validation & Quality
  • Validate models using appropriate testing, back‑testing and comparison techniques.
  • Assess sensitivity to assumptions and changing conditions.
  • Monitor model performance over time and identify concept drift or degradation.
  • Maintain high standards of analytical rigour and reproducibility.
Collaboration & Communication
  • Partner closely with Business Analysts, Engineering, Product and operational teams.
  • Explain modelling…
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