Accelerator - Data Science Internship

Key Skills

Cloud computing, Python Programming, SQL

Job Description

We are an innovative global healthcare company, driven by one purpose: we chase the miracles of science to improve people’s lives. Our team, across some 100 countries, is dedicated to transforming the practice of medicine by working to turn the impossible into the possible. We provide potentially life-changing treatment options and life-saving vaccine protection to millions of people globally, while putting sustainability and social responsibility at the center of our ambitions.

Sanofi has recently embarked in to a vast and ambitious digital transformation program. A cornerstone of this roadmap is the acceleration of its data transformation and of the adoption of artificial intelligence (AI) and machine learning (ML) solutions, to accelerate R&D, manufacturing and commercial performance and bring better drugs and vaccines to patients faster, to improve health and save lives.

Topic of internship description

As part of an international project on a high-impact drug, we seek to improve patient and physician awareness of the drug. The goal is to better understand how to help doctors prescribe this life-changing drug.

To achieve this, we are looking to better understand the communication around this drug and how to educate patients and doctors. An in-depth study will be conducted using the tools of Marketing Mix Modeling, based on Bayesian and causal inference. The main challenges of the approach will be to address a small amount of data, the funnel effect from the patient's awareness of the treatment until it is taken, and finally the selection of the model based on its ability to generalize and the evaluation of its uncertainty. Therefore, the modeling approach will rely heavily on graphical modeling, which allows for a clear view of the causal effect and usage of probabilistic programming.

In close collaboration with the teams in charge of communication, it will also be necessary to translate the complex concepts resulting from this analysis so that its use is as effective as possible, for the benefit of patients.

Key Functional & technical Requirements & Qualifications:

• Master's Degree in mathematics, computer science, engineering, physics, statistics, economics, computational sciences, or a related quantitative discipline
• Expertise with core data science languages (such as Python, R, Scala), and familiarity with different database systems (g., SQL, NoSQL)
• Expertise with in some of the following areas: supervised learning, time series forecasting, Bayesian inference, causal inference, optimization
• Knowledge about STAN is a plus
• Knowledge of some visualization tools (g., Tableau, Power BI, Plotly or similar) is a plus
• Motivated, positive team player
• Problem solving& critical thinking
• Experience in a healthcare company is a strong plus.