Data Scientist Intern

About Aqemia

Aqemia is a next-generation pharmaceutical company generating one of the fastest drug discovery pipelines in the world. Our mission is to develop groundbreaking, fast-acting drug candidates for scores of severe diseases. What sets us apart is our proprietary quantum mechanical and statistical algorithms that power generative artificial intelligence to design new drug candidates.

The velocity and precision of our technology platform allows us to scale drug discovery projects as technology projects.

We’ve grown to a team of over 45 highly motivated and spirited individuals standing at the intersection of Chemistry, Machine Learning, Physics, and Software Engineering.

We are proud to announce that we've raised $12 million from leading VCs.

If this sounds exciting to you, come and join us!

Data Scientist Intern

The difference you’ll make

The Data team's main objective: harness vast volumes of data from multiple scientific disciplines to identify new drug opportunities.

Our Data team:

  • designs, builds and runs our data stack processing large volumes of complex and heterogeneous data  (chemical, biological, medical and physical) from internal and external sources
  • models these wide, complex knowledges in innovative ways (e.g. in a knowledge graph)
  • extracts novel insights, encompassing chemistry and biology complexity, to steer our de novo drug discovery pipelines
  • assesses Aqemia’s core technology by confronting it against external data on numerous aspects and provides areas for improvement

To deliver on this exciting goal, the data team is at the crossroads of the different teams within Aqemia, whether drug discovery or tech teams, and it leverages multiple expertises: 

  • data and software engineering 
  • strong understanding of drug design, chemistry and biology
  • data science

Job description

As a Data Scientist Intern within the data team, you will contribute to deliver on the following goals:

  • design and train cutting edge machine learning models - such as Knowledge Graphs - to identify Aqemia's next targets
  • collaborate with engineers to deploy and maintain models in production in a robust and scalable way

What You’ll Do

You will:

  • propose and build relevant algorithms to:
  • prioritize targets with respect to their biological importance
  • assess their suitability to progress as drugs
  • identify, with the help of Aqemia's scientists, new sources of Data that will feed our ML models
  • tightly collaborate with Aqemia's engineers to deploy and maintain machine learning models in production

Who You Are

You have strong abilities in machine learning and programming combined with a passion for delivering results. 

You possess strong written and verbal communication skills and a high intellectual curiosity with ability to learn new concepts/frameworks and technology rapidly as changes arise. 

You are eager to grow and learn in their expertise and in fields that are core for Aqemia: chemistry, physics and biology.

Our Workplace Environment

Fast-paced, intellectually and scientifically demanding, results-driven.

Our Founders boast:

10+ years experience in research at Ecole Normale Supérieure in Paris, not to mention a stint in Oxford and Cambridge.

10+ years experience in strategy consulting at BCG.

  • Aqemia has a rapidly growing team of +40 people from world-class institutions ( GSK, Sanofi, Cambridge, Ecole Normale Supérieure, Ecole Polytechnique, Ecole Centrale, Mines Paris, EnsiMag, BCG)
  • Our premises are conveniently located in the heart of Paris (1 Bd Pasteur), with a possibility of up to 2 days of remote work.
  • Working language: English

Should you wish to apply for this position please send us your resume at

We are growing fast, if you feel that you don't fit this job description but you’re still excited to join, then please get in touch! 


Aqemia is an Equal Employment Opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion or belief, sex, sexual orientation, gender perception or identity, national origin, age, marital status, disability status or any other basis under applicable law.