General Application — Research & Science

As a researcher at System, you will:

• 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

The ideal candidate has:

• 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

Bonus if you have:

• 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

Compensation: Commensurate with experience and level.