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

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

graph MLGraph Neural Networklink predictionnode classificationexplainability methodsknowledge-graph buildinggraph databasesPythonmachine learningdeep learning

Soft Skills

communicationanalytical skillsproblem-solvingpresentation skills