We are seeking a skilled R&D Data Scientist to join our dynamic team at Quantori. This role will focus on building and applying advanced ML and Data Engineering solutions that accelerate scientific innovation across the drug discovery lifecycle. The candidate should have strong computational expertise and a solid scientific understanding of early R&D, including areas such as Target Identification & Assessment, Lead Identification & Optimization, Mechanistic / Mode of Action studies, and Lab Automation & high-throughput experimentation. The R&D Data Scientist will collaborate closely with discovery scientists, automation engineers, computational biologists, and platform technology teams to transform complex, multimodal R&D data into actionable insights that drive therapeutic innovation.
Location:
Europe, Armenia, Georgia
Responsibilities:
* Develop ML/AI models that support target prioritization, multi-omics integration, and mechanistic inference.
* Apply modern ML approaches (e.g., deep learning, graph learning, foundation models, generative models) to chemical, biological, imaging, and assay datasets.
* Build and optimize models for real-world R&D use cases, ensuring scalability, interpretability, and scientific rigor.
* Design, build, and maintain robust data pipelines that curate, standardize, and integrate diverse R&D datasets (chemical, biological, multi-omics, imaging, biophysical, automation logs, etc.).
* Partner with platform teams to implement best-practice MLOps/DevOps workflows and deploy ML models into production R&D environments
* Develop tooling that accelerates dataset preparation, feature engineering, and model lifecycle management.
* Work hand-in-hand with discovery scientists to understand key biological and chemical questions and shape computational strategy accordingly.
* Translate sparse, heterogeneous experimental datasets into insights that guide decision-making in hit discovery, mechanism studies, perturbation experiments, and compound optimization.
* Participate in design, interpretation, and iterative refinement of discovery experiments.
* Partner with cross-functional teams in R&D Data Science, IT, platform engineering, and therapeutic area groups to drive AI/ML adoption.
* Contribute to evaluating new analytical methods, automation technologies, and data platforms supporting next-generation discovery science.
* Promote high standards for data quality, documentation, governance, and reproducibility.
What we expect:
* Master's or Ph.D. in Computational Biology, Bioinformatics, Data Science, Chemistry, Chemical Biology, Biomedical Engineering, Computer Science, or related fields
* Experience applying ML/AI in scientific domains (drug discovery, biology, chemistry, systems biology, imaging, or related areas)
* Strong Python skills, with experience in scientific and ML libraries (PyTorch, TensorFlow, scikit-learn, RDKit, etc.)
* Practical experience with data engineering, including data modeling, workflow orchestration, ETL/ELT pipelines, and cloud computing environments (AWS, GCP, or Azure)
* Ability to work directly with experimental scientists to solve real R&D challenges
* Strong communication skills and ability to thrive in a matrixed, multidisciplinary environment
* English level B2+ or higher
Nice to have:
* Experience in pharma or biotech discovery, including target assessment, phenotypic screening, medicinal chemistry workflows, and lab automation
* Familiarity with omics, high-content imaging, chemical structure data, or biological assay data
* Knowledge of data standards (e.g., FAIR, ontologies, controlled vocabularies) and working within regulated or quality-governed environments
We offer:
* Competitive compensation
* Remote or office work
* Flexible working hours
* Healthcare benefits: medical insurance and paid sick leave
* Continuous education, mentoring, and professional development programs
* A team with an excellent tech expertise
* Certifications paid by the company