Note: The job is a remote job and is open to candidates in USA. interos.ai provides AI-powered supply chain risk intelligence through its Resilience and iQ platforms, which use knowledge graphs and predictive analytics to help organizations understand and mitigate global risks. The Lead Computational Social Scientist will develop and operationalize quantitative computational social-science, financial, economic, and network models, lead model-driven projects, and translate complex analytical findings into practical insights for technical and non-technical audiences.
Responsibilities
- Research, develop, and implement computational social-science models for integration into the interos.ai platform
- Apply quantitative methods to understand network structures, global supply chain dynamics, and economic and financial risk
- Manage multiple projects and execute rigorous models under tight timelines, while communicating progress across technical and non-technical stakeholders
- Evaluate and validate academic and industry models and assess applicability to product needs
- Translate complex theoretical frameworks into practical, scalable models used by public and private sector customers
- Produce white papers, blogs, and external presentations
- Stay current on global events, emerging datasets, and methodological advances relevant to global financial markets, regulations, and macro-economic trends
- Collaborate across Applied AI, Engineering, and Product to take models from initial concept through to full productization
- Embrace the start-up speed to delivery expectations and communicate and execute within multi-disciplinary scrum teams
Skills
- PhD in political science, economics, or other social or behavioral science, actuarial science, or related quantitative field with 5+ years of experience; or Master's degree with 7+ years; or 10+ years of hands-on experience modeling complex socio-technical or large-scale systems
- Experience thriving in fast-paced, cross-disciplinary environments, especially in start-up or other face-paced product-centric environments
- Deep curiosity and a persistent drive to explore new data, better methods, and novel approaches to complex analytical problems
- Demonstrated expertise in quantitative modeling across social, organizational, or physical systems
- Proven open-source research skills and experience supporting product development
- Strong communication skills with the ability to explain technical concepts to both technical and non-technical audiences
- Proficiency with Python, Jira, Git, LLM coding tools, and related analytical or engineering collaboration tools
- Embody a hungry, humble, and smart mindset: always learning, collaborating, and executing
- This role can be remote-first within the United States, with optional access to our Arlington, VA HQ
- Occasional travel may be required for team summits, customer engagements, or industry events
- Experience operationalizing academic or technical models within private-sector or applied environments
- Ability to communicate effectively with diverse audiences, including internal teams, external partners, technical experts, and business stakeholders
- Background in computational social science, network science, system dynamics, global supply chain analysis, complexity science, or similar domains
- Experience working with engineering and product teams and communicating and translating models for software production
Benefits
- Comprehensive health, dental, and vision insurance
- 401(k) with employer match
- Flexible Time Off (FTO) + 10 paid holidays
- Opportunity to help shape an early, fast-growing market
- A flexible, remote-first work environment that empowers you to perform at your best, wherever you are
- An incredible culture built on trust, accountability, and collaboration across time zones and teams
- Eligible for annual performance bonus
- Stock options included as part of total compensation package
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