Global HEOR Modelling Associate

Global HEOR Modelling Associate Remote-based in Europe, with a preference for Italy. ~10% Travel

Opportunity The Global HEOR Modelling Associate supports evidence generation activities to inform reimbursement, pricing, and market access decisions across Menarini’s portfolio. The role focuses on developing robust health economic and outcomes research (HEOR) analyses and models that demonstrate product value and support business objectives.

Within the Global HEOR function, you will work closely with senior HEOR colleagues to develop economic models and conduct evidence synthesis using modern analytical approaches, with a particular emphasis on the practical application of AI-enabled tools in HEOR. The ideal candidate is a motivated quantitative analyst with strong (bio)statistical foundations and programming expertise.

Main accountabilities Working in close collaboration with senior team members, you will contribute to HEOR modelling and analytics across the following areas: Evidence generation support:

Contribute to the development of cost-effectiveness models, budget impact analyses, and burden-of-illness studies. Biostatistical analysis:

Design and execute statistical analysis plans, including comparative effectiveness research, Matching-Adjusted Indirect Comparisons (MAIC), Network Meta-Analyses (NMA), and survival analyses (including parametric extrapolation). Statistical programming:

Write clean, efficient, well-documented code in

R and/or Python

to automate data cleaning, analysis, and reporting. Use AI-assisted coding tools (e.g., GitHub Copilot) appropriately to optimise workflows while maintaining quality and traceability. Data analysis & forecasting:

Conduct statistical modelling (e.g., regression, predictive modelling) to support forecasting, value assessments, and pricing strategy discussions. Cross-functional collaboration:

Partner with clinical development and other internal stakeholders to integrate real-world evidence (RWE) and clinical evidence into coherent value propositions. Communication & deliverables:

Prepare technical reports, slide decks, model documentation, and market access materials to communicate analytical methods and results to internal teams and external stakeholders. Innovation:

Proactively evaluate and apply new analytical technologies and AI tools to improve efficiency and modelling precision.

Minimum qualifications Education:

Master’s degree (MSc/MPH/MS) in Biostatistics, Statistics, Mathematics, or a related quantitative field. Biostatistics expertise:

Strong foundational knowledge, including: hypothesis testing (parametric and non-parametric) regression analysis (linear, logistic, multivariable) survival analysis (Kaplan–Meier, Cox proportional hazards, parametric survival models) study design and sample size calculation Experience:

2+ years

of experience in HEOR, health economics, outcomes research, or statistical analysis (relevant academic research, internships, consultancy, and/or industry experience considered). Technical skills:

Proficiency in

R and/or Python

for statistical programming. Communication:

Excellent written and verbal English; ability to explain technical concepts to non-technical audiences. Mindset:

Strong analytical problem-solving skills, attention to detail, and a demonstrated willingness to learn new methodologies. Values:

Alignment with company values: Patient Focus, People Care / Passion, Urgency to Act, Team Player, Operational Excellence & Quality, Responsibility & Integrity.

Preferred qualifications AI & innovation:

Demonstrated interest in applying AI tools (e.g., large language models, generative AI, coding assistants) to improve analytical efficiency and problem-solving. Advanced education:

PhD in a quantitative discipline (e.g., Statistics, Biostatistics, Health Economics). Advanced modelling:

Exposure to machine learning (e.g., gradient boosting such as XGBoost), mixture cure models, and/or causal inference methods. HTA knowledge:

Understanding of HTA processes, pharmacoeconomic guidelines, and cost-effectiveness analysis requirements. Big data:

Exposure to SQL, Spark, and/or cloud platforms. Therapeutic area:

Experience in or exposure to Oncology. Publication:

Experience preparing manuscripts, posters, or conference presentations.

Menarini Group is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.