Data Scientist

Ipsen is a dynamic and growing global specialty-driven biopharmaceutical company focused on innovation and specialty care.

We aim to make a sustainable difference by significantly improving patients’ health and quality of life and providing them with effective therapeutic solutions for unmet medical needs through differentiated and innovative medicines in Oncology, Neurosciences and Rare Diseases.

The patient is at the heart of everything we do, and we also care for our employees because they are the ambassadors who truly make the difference. We attract and develop bold, agile, entrepreneurial individuals who take full ownership of their decisions; leaders drawn by a purpose to make a direct impact through their work in people’s lives.

We offer employees a wealth of fulfilling challenges & growth opportunities, and the chance to contribute within a fast-moving organisation, an organisation that is genuinely game-changing.

The Data Scientist will design and implement advanced data science and AI solutions to address scientific and operational challenges within R&D and Medical functions.

This includes developing patient analytics capabilities, applying machine learning and statistical modeling, and integrating cutting-edge technologies such as NLP, large language models (LLMs), and generative AI into core processes.

The role involves close collaboration with cross-functional teams to enhance evidence generation strategies, optimize decision-making, and support therapeutic area initiatives in Oncology, Rare Diseases, and Neuroscience. A strong understanding of healthcare data ecosystems and the ability to translate complex data into actionable insights are essential.

This position contributes to the enterprise-wide digital transformation by building scalable, high-impact analytical tools and fostering innovation across the portfolio.

Main Responsibilities

Data Science & Analytic Capabilities Building:

• Develop analytic and data science solutions that support a broad range of strategic and operational needs across R&D and Medical
• Apply and test various data science approaches that improve operational efficiencies and accelerate and scale evidence generation capabilities, while ensuring scientific robustness.
  
  

Evidence Generation

• Develop data engineering pipelines that supports analytics and visualization needs for variety of data sources containing patient-level data, such as healthcare claims, EMRs, PROs, omics, etc.
• Conduct analyses of various patient data sets that supports internal decision-making and evidence generation.
  
  

Stakeholder Engagement

• Support the development of analytic and data science solutions (e.g., ML, NLP, data visualization) by working with internal teams and leveraging diverse data sources (e.g., EMR/EHR, claims, PROs, scientific literature).
• Work closely with cross-functional teams within R&D and Medical Affairs to gather requirements and contribute to the design and implementation of data-driven solutions.
  
  

Continuous Learning And Innovation

• Stay abreast of advancements in data science, machine learning, and healthcare technologies;
• Educate and raise awareness around Data Science and its potential in supporting Ipsen’s internal teams to generate buy-in across the organization;
  
  

In order to be considered for this role you must have:

• Advanced degree (Ph.D. or Master's) in Data Science, Computer Science, Statistics, or a related field.
• Experience in analytic/data science roles within pharma.
• Strong methodological and analytical skills with regard to machine learning, deep learning, NLP and other AI approaches. Proven experience applying these approaches in healthcare space.
• Solid understanding of statistical analysis and hypothesis testing
• Proficient in programming languages such as Python and/or R, with a focus on healthcare data science
• Proven experience working with patient-level Real World Data, medical data and a strong understanding of healthcare systems.
• Strong communication skills and the ability to convey complex technical concepts to diverse audiences
• English fluency.