Expert Data Scientist (single-cell and integrative omics)

Major accountabilities:

• Leverage single-cell and spatial transcriptomics data to nominate targets and elucidate therapeutic mechanisms, while elevating insights via large-scale meta-analysis and integration with multimodal data (genetics, proteomics, imaging). 

• Enhance molecular disease understanding and hypothesis generation through the application of advanced network biology to integrate omics data into known and inferred networks, including intracellular regulation and cell-cell communication. 

• Apply cutting edge deep learning techniques that take advantage of the increased data content from single-cell techniques, in pursuit of robust in silico perturbations, interpretable feature spaces, and generative modeling. 

• Ideate and collaborate on experimental designs that would provide industry-leading information content, such as patient cell atlases, emergent molecular / proteomic techniques, and single-cell perturbation / protein profiles. 

• Serve as a bridge between valuable data assets and project teams to enrich early preclinical hypothesis generation, in close collaboration with data scientists with complementary expertise (e.g., cheminformatics, imaging analysis, protein structural informatics). 

Role requirements: 

• Master's or PhD with a bioinformatics / computational biology focus; alternatively, a degree in a quantitative subject (e.g. computer science, data science, physics) in combination with demonstrable experience in life sciences / drug discovery. 

• Experience in handling genome-scale data types. Strong preference for experience in single-cell or spatial transcriptomics. 

• Demonstrated ability to integrate data across data modalities to answer scientific questions and formulate new biological hypotheses. 

• Excellent scientific communication, including the ability to present complex data science concepts in digestible terms to diverse scientific audiences while leveraging innovative data visualization. 

• Demonstrated ability to work as part of an interdisciplinary team (i.e., biologists, chemists, data scientists), with proactive and results-oriented communication skills.  Dedication to promoting mutual respect, empathy, and positivity in diverse professional settings. 

• Expertise working in Linux high performance computing and cloud environments. 

• Expertise in Python / R scientific stacks, familiarity with best practices in computational reproducible research (version control, testing, documentation). 

• Experience identifying, curating, and integrating data from internal and external sources including major public databases (e.g. NCBI, UniProt, and others). 

Novartis is committed to building an outstanding, inclusive work environment and diverse teams representative of the patients and communities we serve.