interos.ai · 1 week ago
Principal Computational Social Scientist
United States
Full-time
Remote
Senior Level, Lead/Staff
$150K/yr - $200K/yr
5+ years expInteros.ai is defining the category of supply chain risk intelligence, building the world’s most trusted and transparent supply chains. The Principal Computational Social Scientist will apply quantitative social-science methods to analyze global supply chains and organizational behavior, while collaborating with various teams to operationalize complex models at scale.
Artificial Intelligence (AI)Cyber SecurityMachine LearningRisk ManagementSaaSSupply Chain Management
No H1B
Responsibilities
Research, develop, and implement computational social-science models for integration into the Interos platform
Apply quantitative methods to understand network structures, global supply chain dynamics, and socio-technical behaviors
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 research papers, white papers, blogs, and external presentations
Stay current on global events, emerging datasets, and methodological advances relevant to computational social science
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
Qualification
Required
PhD in a social, behavioral, actuarial, computer, 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
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
Experience thriving in fast-paced, cross-disciplinary environments
Proficiency with Python, Jira, Git, and related analytical or engineering collaboration tools
Embodies a hungry, humble, and smart mindset: always learning, collaborating, and executing
Preferred
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 teams and communicating and translating models for software production
Benefits
Comprehensive health, dental & vision insurance
401(k) with employer match
Flexible Time Off (FTO) + 10 paid holidays
Career growth opportunities and opportunity to help shape an early, fast-growing market
Employee referral bonuses and recognition programs
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
Company
interos.ai
interos.ai is the Supply Chain Risk Intelligence company — building the most trusted and transparent supply chains in the world.
51-200 employees
Funding
Current Stage
Growth StageTotal Funding
$174.85MKey Investors
Blue OwlBroadway AngelsAccenture Ventures
2024-10-24Private Equity· $40M
2023-12-20Series Unknown
2022-09-21Series Unknown
Leadership Team
Ted Krantz
Chief Executive Officer, Board Director
Andrea Little Limbago
Senior Vice President, Applied AI
Recent News
2025-08-22
Company data provided by crunchbase