Ipsen is looking to design and implement advanced data science and AI solutions to address scientific and operational challenges within R&D and Medical functions, including developing patient analytics capabilities, applying machine learning and statistical modeling, and integrating cutting-edge technologies into core processes to enhance evidence generation strategies, optimize decision-making, and support therapeutic area initiatives.
Requirements
- 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.
- 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.
Responsibilities
- design and implement advanced data science and AI solutions to address scientific and operational challenges within R&D and Medical functions.
- 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.
- 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.
- 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.
- 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).
Other
- 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.
- 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.
- 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;
- Strong communication skills and the ability to convey complex technical concepts to diverse audiences
