Staff Data Scientist, Graph ML
Job Description:
• Develop and deploy graph ML solutions to synthesize and extract novel insights from Valo data in the context of a vast corpus of knowledge in medicine, molecular biology, human genetics, and drugs, to drive compute-enabled biological hypothesis generation.
• Collaborate closely with a diverse group of data scientists and biologists to enable the contextualization of predicted drug targets within relevant patient subpopulations.
• Communicate methodological approaches and key results to internal and external cross-functional stakeholders.
• Work with other data scientists, software engineers, and data engineers to continue building and improving Valo’s integrated graph platform to accelerate insights across multiple projects and applications.
Requirements:
• MS or PhD in a quantitative field with extensive experience at the intersection of machine learning and graph analytics
• Experience in healthcare, medicine, molecular biology, computational biology, or life sciences.
• Advanced knowledge of and experience with graph ML techniques such as Graph Neural Network (GNN) models applied to link prediction, node classification, and other biomedical-relevant computational tasks, as well as related explainability methods
• Experience or general knowledge of knowledge-graph building and graph databases
• Familiarity with general graph algorithms and relevant Python libraries
• Strong experience in Python and machine learning and/or deep-learning frameworks (e.g., pytorch)
• Experience with data science best practices (data provenance, code versioning, reproducibility, git, etc), large-scale data analytics engines (e.g., Spark or Dask), and working in cloud environments (e.g., AWS)
• Strong data visualization, analytical, problem-solving, and communication skills, with demonstrated ability to condense, summarize, and synthesize results into informative and actionable presentations to experts from different fields.
Benefits:
• healthcare coverage
• annual incentive program
• retirement benefits
• broad range of other benefits
Apply Now
Apply Now
• Develop and deploy graph ML solutions to synthesize and extract novel insights from Valo data in the context of a vast corpus of knowledge in medicine, molecular biology, human genetics, and drugs, to drive compute-enabled biological hypothesis generation.
• Collaborate closely with a diverse group of data scientists and biologists to enable the contextualization of predicted drug targets within relevant patient subpopulations.
• Communicate methodological approaches and key results to internal and external cross-functional stakeholders.
• Work with other data scientists, software engineers, and data engineers to continue building and improving Valo’s integrated graph platform to accelerate insights across multiple projects and applications.
Requirements:
• MS or PhD in a quantitative field with extensive experience at the intersection of machine learning and graph analytics
• Experience in healthcare, medicine, molecular biology, computational biology, or life sciences.
• Advanced knowledge of and experience with graph ML techniques such as Graph Neural Network (GNN) models applied to link prediction, node classification, and other biomedical-relevant computational tasks, as well as related explainability methods
• Experience or general knowledge of knowledge-graph building and graph databases
• Familiarity with general graph algorithms and relevant Python libraries
• Strong experience in Python and machine learning and/or deep-learning frameworks (e.g., pytorch)
• Experience with data science best practices (data provenance, code versioning, reproducibility, git, etc), large-scale data analytics engines (e.g., Spark or Dask), and working in cloud environments (e.g., AWS)
• Strong data visualization, analytical, problem-solving, and communication skills, with demonstrated ability to condense, summarize, and synthesize results into informative and actionable presentations to experts from different fields.
Benefits:
• healthcare coverage
• annual incentive program
• retirement benefits
• broad range of other benefits
Apply Now
Apply Now