System - General Application — Research & Science
Requirements
• Master's or PhD in Computer Science, Statistics, Biomedical Informatics, or a related field • A strong publication record or equivalent applied research experience • Deep expertise in machine learning, statistical modeling, or computational methods • Experience working with complex, heterogeneous, or graph-structured data • Ability to communicate research findings clearly to both technical and non-technical audiences • Comfort operating in a fast-paced startup environment alongside a long research horizon • Experience with clinical NLP, EHR data, or healthcare ontologies (SNOMED, ICD, OMOP) • Familiarity with knowledge graphs, semantic web technologies, or ontology engineering • Background in causal inference, systems dynamics, or complex adaptive systems • Experience collaborating with clinicians, policymakers, or public health researchers • You might be a fit if you: • Think in systems — mapping feedback loops, interdependencies, and second-order effects comes naturally to you • Are motivated by purpose-driven work, particularly at the intersection of technology and healthcare • Believe technology should be a force for good and are drawn to the Public Benefit Corporation model • Hold yourself and your work to a values-first standard, not just a deliverables-first one • Lead with first principles and are comfortable questioning assumptions others take for granted • See complexity as an invitation, not an obstacle — you thrive when problems are messy and interconnected • Care about the downstream effects of what you build — on users, on systems, on society • Operate with intellectual humility — always learning, always open to being wrong • We aspire to help the world see itself differently and build a more responsible and values-driven model of a tech company. We are backed by top-tier VCs in Silicon Valley and New York and leading angel investors and founded by the former VP Data at Spotify. To learn more about what motivates our social mission, we invite you to read our blog here. • We believe in the power of autonomous, interdisciplinary, and diverse teams; in agile development; and in leading with values, first principles, and clear high-level priorities backed by data. We believe in cultivating a growth mindset for our team — always learning, improving, being challenged, and having opportunities for professional and personal development.
Responsibilities
• Develop and validate novel methods for modeling complex, interconnected systems • Work at the intersection of graph theory, machine learning, and domain-specific knowledge • Collaborate with Data Science and Engineering to transition research findings into production • Publish and present findings that advance both the field and System's mission • Partner with clinical and domain experts to ground research in real-world impact • Contribute to a culture of intellectual rigor, curiosity, and continuous learning
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