Data Scientist - Drug Discovery & AI

Join Excelya, where Audacity, Care, and Energy define who we are and how we work. We believe in creating bold solutions and fostering an inclusive environment where collaboration and individual growth go hand in hand.

This role is an exciting opportunity to contribute to a dynamic, ambitious team in Data Management. You will play a critical part in driving innovation and making an impact in the clinical research space, while enjoying a stimulating professional environment that encourages personal and intellectual growth.

We are looking for experienced Data Scientists to support innovative Drug Discovery programs within a leading pharmaceutical research environment.

The selected candidates will work with multidisciplinary teams including biologists, chemists, data scientists and project leaders to accelerate therapeutic projects through data-driven and in silico approaches.

Main Responsibilities

• Integrate and analyze large and heterogeneous scientific datasets.
• Develop and maintain data processing and data preparation pipelines.
• Build and deploy Machine Learning and predictive models.
• Apply AI approaches to biological and pharmaceutical research challenges.
• Develop mathematical and systems biology models to support decision-making.
• Contribute to in silico drug design, molecular selection and optimization activities.
• Perform scientific literature reviews and support research projects with data-driven insights.
• Collaborate closely with biology, chemistry and translational medicine teams.

Do you have experience in Python?, Do you have a Doctoral degree?, At Excelya, taking audacious steps is encouraged, so we’re looking for individuals who are ready to grow with us and share our values.

• Experience: Minimum 3 years of experience. Experience working in pharmaceutical, biotech, CRO or research environments. Strong analytical and problem-solving skills. Ability to work in multidisciplinary and international teams.
• Education: MSc, PhD or equivalent in Bioinformatics, Computational Biology, Data Science, Applied Mathematics, Computational Chemistry or related field.
• Languages: Fluency in English (mandatory). Fluency in French is a plus
• Skills:

Scientific Expertise

• Bioinformatics
• Computational Biology
• Computational Chemistry
• Pharmacology
• Data Science applied to Drug Discovery
• Artificial Intelligence and Machine Learning
• Predictive Modelling
• Mathematical Modelling
• Systems Biology

Technical Skills

• Strong Python programming skills
• Data integration and data processing
• Experience with large scientific datasets
• Knowledge of RNA/DNA sequence analysis is a plus
• Knowledge of protein engineering and drug design is a plus

Nice to Have

• Experience in AI for Drug Discovery
• Experience in translational research
• Experience in oncology or other therapeutic areas
• Exposure to cloud computing environments
• Publication record in scientific research

At Excelya, we combine passion for science with enthusiasm for teamwork to redefine excellence in healthcare.

Here’s what makes us unique.

We are a young, ambitious health company representing 900 Excelyates, driven to become Europe’s leading mid-size CRO with the best employee experience. Our one-stop provider service model - offering full-service, functional service provider, and consulting - enables you to evolve through diverse projects. Working alongside preeminent experts, you will help improve scientific, operational, and human knowledge to enhance the patient’s journey.

Excelling with Care

At Excelya, Care lies at the heart of what we do. We provide equal opportunities for all and foster a diverse, equitable, and inclusive workplace where humility and boldness work hand in hand. Everyone has a space to feel valued, thrive, and collaborate with purpose.

Your challenges become our shared mission. Together, we transform bold ideas into reality, the Excelya way.

Watch our testimonial video to hear directly from our Excelyates about why Excelya is more than just a workplace-it’s a community built on values.