Medical Data & Insights Consultant

Quinten Health is recruiting a Medical Data and Insights Consultant to join the Healthcare team, working in close collaboration with Data Scientists, Biostatisticians, and Project Managers. You will be supported by two senior medical data and insights consultants.

You might be involved in a project such as:

• Identify risk factors of disease progression to personalize treatment pathways;
• Identify sub-groups of patients who are better responders to a treatment;
• Predict long‑term risk of exacerbation to anticipate the design of trials;
• Simulate long‑term treatment effect scenario to bridge efficacy to effectiveness.

Key Responsibilities

1. Working in collaboration with the team of data science engineers to assess the fitness of Real‑World databases, provide clinical and scientific input to support analytical work (e.g., modeling), capture clinical characteristics in real‑world databases, including finding proxies for clinical events and/or scores, time windows for data capture, define the target study population, outcome of interest, covariates, and confounders, provide code lists for diagnosis, treatments, procedures, structure the data to ensure the quality of the analysis from a medical point of view (e.g., capture and interpret chronic and acute diseases differently), develop variable derivation strategies to extract a maximum of information from data (e.g., therapeutic escalation to measure a patient’s severity), adapt the analytical strategy to align the results with the medical objectives of the project, interpret the output of analyses, assess findings, and provide relevant insights based on existing literature, write reports and scientific publications to communicate study results, give input on the scientific aspects of projects, coordinating with data scientists, epidemiologists, statisticians, and project managers, perform necessary administrative functions and additional tasks as required.
2. Supporting the Project Managers in the engagement of customers to provide pharmaceutical competitive intelligence and portfolio screening to support project business strategy, engage with clients, with senior staff involvement for understanding the strategic needs of the client and translating them into actionable solutions.
3. Contributing to the innovation and development activities of the organization to perform literature reviews on a therapeutic area or disease to identify and describe unmet needs, pathophysiology, standard of care tailored to the specific activity, assess potential data sources and partnerships to support the development of disease and care models, engage with scientific or medical KOLs to provide relevant insights and validation of internally developed disease and care models, participate in company‑sponsored training programs as required to ensure that skills are learned, maintained, and focused accordingly.

Qualifications

• Medical, Pharm D degree, PhD or Master’s Degree in life sciences (pharmacology, physiology, cognitive, etc.).
• First working experience (excluding internship and/or apprenticeship) in a relevant professional area (e.g., in the pharmaceutical industry, medical writing, academic or clinical research, or health‑related consulting or real‑world evidence (RWE) projects).
• Knowledge of pharmaceutical industry, healthcare regulation, clinical development processes, and medical practice.
• Client‑facing mindset with good communication; ability to lead discussions and act as a subject matter expert in interactions with clients.
• Experience contributing to clinical research projects, including clinical trials, observational studies, cohort studies, baseline assessments, and study design activities.
• Professional proficiency in English, written and spoken.
• Ability to work effectively both independently and as part of a team.
• Strong organizational skills, with the ability to prioritize and manage multiple tasks and projects.
• Ability to make decisions and think strategically.
• Experience with claims databases or electronic health records (such as SNDS, CPRD, HES, sickness funds data, national or disease registries).
• Experience in epidemiology.
• Basic knowledge of programming (e.g., R, Python, PySpark) is valued to facilitate dialogue around statistical analyses and the interpretation of tables and figures.
• Knowledge of statistical and machine‑learning methods.
• Experience in the analysis of -omics (RNA expression, genetic analyses, etc.).