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Pierre Fabre

Senior Data Scientist – Multi‑omics AI & Target Identification - CDI

Haute Garonne (31)

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hirly's read of this role

Role family
Data & ML
Seniority
Senior
Country
FR
Work mode
On-site / unstated
First seen by hirly
1 Sept 2026

Derived automatically from the posting. Upload your resume above to see how the role scores against it.

the posting

Who we are ?

  • We are Pierre Fabre Laboratories, a global leader combining pharmaceutical expertise with dermo-cosmetics to support consumers and patients at every stage of their care journey.
  • Our portfolio includes several medical franchises and international brands such as Eau Thermale Avène, Ducray, A-Derma, Klorane, René Furterer, and Pierre Fabre Oral Care.
  • By joining us, you become part of a meaningful company where the human dimension is essential. You become a participant in the "We Care Movement," a movement that values excellence and innovation within passionate teams. Together, we push the boundaries of science to unite health and beauty for the benefit of all, because Every time we care for a single person, we make the whole world better.

Present in 120 countries with a team of over 10,000 employees, we are proud to create a scientific and human impact, today and tomorrow! If caring is at the heart of your values, join Pierre Fabre Laboratories and become a key player in the “We Care Movement".

Your mission

We are seeking in Toulouse (Oncopole- Langlade Location) a talented and highly motivated Senior Data Scientist - Multi ‑ Omics AI & Target Identification with strong expertise in multi‑omics analysis, machine learning, and AI for biological data to accelerate target identification, translational research, and precision medicine strategies.

As a key member of the Data Science & Biometry Department within Pierre Fabre R&D Medical Care, you will design and develop AI systems capable of learning from high‑dimensional biological data (genomics, transcriptomics, proteomics, functional screens) to deepen disease understanding, uncover pathway‑level mechanisms, and reveal cancer vulnerabilities across indications.

This role sits at the interface of AI research, computational biology, and drug discovery, and is embedded within the Methods & Innovation team, responsible for cross‑functional initiatives involving advanced AI methodologies.

Your role within a pioneering company in full expansion:

Key Responsibilities

  • Develop and apply machine learning and deep learning models to integrate multi‑omics data for target identification and prioritization.
  • Contribute to biological and disease understanding by identifying molecular mechanisms, pathways, and vulnerabilities across cancer indications.
  • Support diverse downstream assessments, including target discovery, toxicity prediction, and patient stratification.
  • Design and train advanced models leveraging representation learning, self‑supervised learning, and domain adaptation.
  • Apply and adapt transformer‑based architectures to biological and omics data.
  • Ensure strong standards for model robustness, reproducibility, interpretability, and scientific validity.
  • Work with HPC and/or cloud environments to scale model training and experimentation.
  • Collaborate closely with biologists, translational scientists, and drug discovery teams to translate biological questions and hypotheses into AI‑driven solutions.
  • Contribute to shared AI frameworks and reusable methodological components across R&D.

This position is based in Toulouse with flexibility for remote work.

We offer an attractive remuneration/benefits package: Incentives, profit-sharing, Pierre Fabre shareholding with matching contribution, health and provident insurance, 16 days of holidays (RTT) in addition to 25 days of personal holidays, public transport participation.

Who you are ?

Your skills at the service of innovative projects:

Education

PhD or Master’s degree in Data Science, Computational Biology, or a related field.

Experience

  • 5+ years of experience in data science applied to life sciences.
  • Demonstrated experience in multi‑omics data analysis for target discovery or translational research.
  • Hands‑on experience developing machine learning and deep learning models.

Technical Skills

  • Strong proficiency in Python.
  • Experience with deep learning frameworks (e.g., PyTorch ).
  • Solid knowledge of modern ML approaches, including transformers, representation learning, self‑supervised learning, and domain adaptation.
  • Familiarity with HPC and/or cloud computing environments.
  • Strong grounding in bioinformatics, cancer biology, and pathway-level reasoning.

Soft Skills & Mindset

  • Strong analytical and structured thinking.
  • Ability to translate biological, scientific, and strategic challenges into effective AI solutions.
  • Excellent cross‑functional collaboration skills.
  • High intellectual curiosity and innovation mindset.
  • Professional proficiency in English (written and oral).

At Pierre Fabre Laboratories, we believe that our greatest asset is our people.

We are committed to a policy of Equal Employment Opportunity and will not discriminate against an applicant or employee based on race, color, religion, creed, national origin or ancestry, sex, sexual orientation, gender identity or expression, age, physical or mental disability, veteran or military status, genetic information, or any other legally recognized protected basis under federal, state, or local law. The information collected by this application is solely to determine suitability for employment, verify identify, and maintain employment statistics on applicants. Applicants with disabilities may be entitled to reasonable accommodation under the Americans with Disabilities Act and certain state or local laws. Please inform the company’s personnel representative if you need assistance completing this application or to otherwise participate in the application process. Thus, we commit to considering all applications equally, without fail.

Original posting on Pierre Fabre's site ↗

Listed on hirly, a job board. hirly is not the employer: Pierre Fabre is hiring for this role.

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