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# Senior Data Scientist - Multi-Omics AI & Target Identification

- **Company:** Pierre Fabre Dermo-Cosmetique USA, Inc.
- **Location:** Toulouse, KY, United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Analysis, Cloud Computing, Computational Biology, Python (Programming Language), Machine Learning, Pytorch, Transfer Learning, Deep Learning, Feature Extraction, Unsupervised Learning
- **Published:** October 16, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/ps07csw5t0

## About the Role

* PhD or Master's degree in Data Science, Computational Biology, or a related field.
 * 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 frame_works (_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).

## Description

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., * 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.