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Interos.ai is seeking a Principal Computational Social Scientist to advance financial and economic modeling capabilities for their supply chain risk intelligence platform. The role sits within the Applied AI team and focuses on developing computational social-science models that analyze global supply chains, financial markets, network dynamics, and macro-level socio-economic trends.
Key responsibilities include researching and implementing quantitative social-science models for platform integration; applying network analysis and economic methods to understand supply chain dynamics and financial risk; managing multiple projects with tight timelines while communicating progress across technical and non-technical stakeholders; evaluating academic and industry models for product applicability; translating theoretical frameworks into scalable, production-ready models; producing research outputs (white papers, blogs, presentations); staying current on global events, datasets, and methodological advances; and collaborating with engineering and product teams to move models from concept through productization.
The ideal candidate holds a PhD in political science, economics, actuarial science, or related quantitative social/behavioral science with 5+ years of experience (or Master's with 7+ years, or 10+ years of hands-on modeling experience). Required skills include expertise in quantitative modeling of complex socio-technical systems, proficiency in Python, Git, Jira, and LLM coding tools, strong research and open-source skills, and demonstrated ability to communicate technical concepts to diverse audiences. Experience operationalizing academic models in applied/private-sector environments is a plus. The role demands comfort with ambiguity, fast-paced execution, cross-disciplinary collaboration, and a mindset of continuous learning.
