Senior Expert I, Data Science

What you'll do

• Analyze and interpret high-dimensional biological data like RNA-seq, DNA-seq, and CRISPR results to inform project decisions.
• Lead profiling strategies for genomic and phenotypic screening data to support patient stratification and identify mechanisms of resistance.
• Integrate multi-modal internal and external preclinical datasets to generate translationally relevant insights for drug development.
• Apply advanced bioinformatics and machine learning techniques to uncover novel biological insights and therapeutic hypotheses.
• Develop and implement innovative analytical methods to visualize and interpret multi-dimensional data from emerging technologies.
• Use data mining and genomic profiling to identify new targets for induced proximity modalities.
• Communicate complex scientific findings and integrative analyses clearly to cross-functional teams and stakeholders.

What we're looking for

• PhD in Computational Biology, Systems Biology, Bioinformatics, Data/Computer Science, or a related field.
• Strong knowledge of cancer biology and multi-modal data types including genomics, transcriptomics, proteomics, and phenotypic screening.
• Proficiency in programming languages such as Python or R within a UNIX/Linux environment with version control and reproducible workflows.
• Demonstrated statistical rigor and analytic depth in analyzing high-dimensional omics datasets like bulk and single-cell transcriptomics.
• Experience leveraging AI-assisted coding tools and LLM-based workflows to accelerate data analysis and model development.
• Familiarity with data workflows for preclinical biomarker discovery and validation.
• Excellent communication skills to convey complex scientific concepts to diverse audiences.
• Fluency in English, both written and verbal.