Senior Data Scientist - Neuroscience Spatial Multi-omics

Requirements

• Outstanding scientific caliber with strong capabilities to identify key analytic questions and formulate rigorous data analytic plans to address critical scientific needs of drug discovery programs.
• Good understanding of neurobiology, particularly neurodegenerative diseases.
• Familiarity with large public single-nucle

Benefits

Additional Information

Job Description Our Company's Data, AI & Genome Sciences Department in Cambridge, MA is seeking a Senior Specialist (Senior Scientist), Data Science to join the Translational Neuroscience Analytics team and drive integrative analysis of spatial and single-nucleus multi-omics data from patients with neurodegenerative diseases. The qualified individual will be a motivated data scientist or computational biologist with a track record of developing and applying cutting-edge AI/ML methodologies to extract actionable insights from single-nucleus and spatial multi-omics data. In this role, they will leverage spatially resolved transcriptomics data with single-cell resolution to understand target pathway biology in relation to pathological hallmarks of neurodegenerative diseases, especially Alzheimer's disease, and integrate this information with single-nucleus multi-omics data from large patient cohorts to enable causal modeling and prediction of target perturbation effects across cell populations of interest. Through these analyses, they will contribute to the evaluation of specific therapeutic hypotheses as well as the identification and placement of biomarkers along the causal cascade from therapeutic target to clinical outcome, ultimately shaping the translational strategies of our neurodegenerative therapeutic programs. They will work alongside with other data scientists and AI/ML scientists in the department to develop and apply innovative approaches to perform such analyses and further integration with clinical, genetic, and other omics data types. They will also be closely collaborating with cross-functional teams of data scientists, bench biologists, and clinical colleagues to drive our neuroscience biomarker and translational strategies. Primary responsibilities: Build and deploy analytic workflows leveraging state-of-art computational methods to analyze spatial multi-omics datasets, with a specific focus on target MOA evaluation and biomarker discovery in neurodegenerative diseases. Formulate and drive integration of spatial and single-nucleus multi-omics data to build unified predictive framework capturing the interactions among different CNS cell types (e.g., neurons and microglia). Lead data analytic projects to evaluate therapeutic hypothesis, drive precision biomarker discovery, inform translational strategies, and enable data-driven decision-making of multiple neuroscience drug discovery programs. Collaborate with internal AI/ML teams to develop and incorporate new methodologies into existing frameworks to enhance data analysis capabilities. Work with experimental biologists, functional area experts, and clinical scientists to support drug discovery and development programs at various stages. Provide data science / computational biology input in research strategy, experimental design, provide data analytical input, and assist in interpreting results from both in-vitro and in-vivo studies. Communicate data analytic results effectively to project teams, key stakeholders, as well as the wider scientific community through written and verbal means, including proposals for further experiments, presentations at internal and external meetings, and publications in leading journals. Required Qualifications: PhD in Data Science, Computational Biology, Computer Science, Genetics/Genomics, Biophysics, Bioinformatics, Statistics, Neuroscience, Neurology, or a related STEM discipline and 0+ years of experience, or an MS and 5+ years of experience. Deep understanding of computational methodologies for single-cell and spatial transcriptomics analysis and extensive experience in their applications, preferably in neurological disorders. Extensive experience in analyzing spatial transcriptomics data with single/sub-cell resolution (e.g., CosMx, Visium HD). Demonstrated expertise in leveraging advanced AI/ML models (e.g., transformers, foundation models) and in silico perturbation simulation. Ability to critically evaluate and apply novel data analysis methods in translational applications. Proficient in one or more programming languages (e.g., Python, R), HPC environments and/or cloud-based platforms, as well as version control systems (e.g., Github). Strong problem-solving skills, self-motivated, attention to detail, and ability to handle multiple projects. Extensive experience to conduct research in a collaborative environment and excellent ability to communicate scientific questions, methodologies, findings and insights. Proven track record (e.g., peer-reviewed publications) of extracting actionable insights from analysis of spatial/single-cell omics data.

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Company Intel

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