Lead Computational Climate Scientist

interos.ai; Remote; CAD 208,000 - 251,000; Full time

Job summary

A supply chain risk intelligence company is seeking a Lead Computational Climate Scientist to develop models assessing climate change impacts on global supply chains. This remote role requires a PhD or significant experience in climatological risk modeling. The position offers a competitive salary between $150,000 and $180,000, along with equity options and career growth opportunities. Candidates should possess strong analytical skills, familiarity with Python, and the ability to work across disciplines in a fast-paced environment.

Benefits

401(k) with employer match

Flexible Time Off (FTO)

Employee referral bonuses

Remote-first work environment

Qualifications

• PhD or 10+ years of experience in modeling climatological risk.
• Proven open-source research skills and product development experience.
• Demonstrated curiosity and persistence in improving methods.

Responsibilities

• Research and implement computational catastrophic risk models.
• Drive geospatial modeling efforts in collaboration with teams.
• Translate theoretical research into practical models for risk.

Skills

Python

Quantitative analysis

Multi-disciplinary collaboration

Education

PhD in atmospheric and oceanic science or related quantitative field

Tools

Jira

Git

Job description

Position:Lead Computational Climate Scientist

Location:Remote

Job Id:341

# of Openings:1

Role:Lead Computational Climate Scientist

About interos.ai

interos.ai is defining the category of supply chain risk intelligence, building the world’s most trusted and transparent supply chains. Our pioneering platform automates the discovery and continuous monitoring of supply chain risk across every tier — enabling faster, data-driven threat mitigation and resilience at global scale. As the first and only automated supplier intelligence platform, interos.ai gives organizations real-time visibility into extended supply chains to protect against regulatory exposure, unethical labor, cyber threats, and systemic vulnerabilities — all under a single pane of glass. With customers across the commercial, government, and public sectors — including Global Fortune 500 enterprises and members of the Five Eyes nations — interos.ai offers a unique opportunity to help shape an early, fast-growing market that’s transforming global security and economic resilience.

The Opportunity

Are you constantly exploring more data-driven and rigorous approaches for analyzing global climatological, societal, technological, and economic disruptions? Do you find yourself transforming complex catastrophic risk models into insights that inform decisions across public and private sector environments? Are you looking to apply these capabilities in a high-growth, early-stage company focused on supply chain risk?
If so, Interos is seeking a Lead Computational Climate Scientist to drive the next evolution of our climate- and disaster-focused modeling capabilities. In this role, you will serve as the core scientific lead for catastrophic risk modeling — overseeing theory- and data-driven quantitative models that assess the impacts of climate change, natural disasters, and industrial and technological disruptions on global supply chains. You will bring both scientific rigor and product-minded execution — building computational models, validating diverse academic and industry frameworks, and assessing applicability to real-world use cases. As part of Interos’ Methodology organization, you will guide model-driven projects from research through full productization. You will collaborate closely with engineering and product teams, operationalize complex models for private- and public-sector customers, and help shape how the Interos platform evaluates climate-driven supply chain risk.

What You Will Do

• Research, develop, and implement computational catastrophic risk models focused on climate change, natural disasters, and technological and industrial disruptions
• Drive geospatial modeling efforts at the grid-cell level and coordinate with product and engineering on geospatial workflows and solutions
• Evaluate and validate diverse academic and industry models and assess applicability to product needs and customer use cases
• Translate theoretical research into practical, scalable models applied to global supply chain risk
• Collaborate across Methodology, Engineering, and Product to take models from concept through to full productization
• Produce research papers, white papers, blogs, and external presentations
• Stay current on global events, emerging datasets, and methodological advances related to climatology, catastrophic risk, and socio-technical system disruptions
• Communicate complex modeling components and frameworks to both technical and non-technical audiences in fast-paced, multi-disciplinary environments

What You Bring

• PhD in atmospheric and oceanic science, physics, social or behavioral science, or related quantitative field; or 10+ years of hands‑on experience modeling and operationalizing climatological or natural disaster risk models
• Experience working within multi-disciplinary teams and managing multiple concurrent projects and priorities
• Demonstrated curiosity and persistence in pursuing better data, improved methods, and novel analytical solutions
• Strong interest in applying scientific modeling to complex physical and socio-technical systems, with an emphasis on climate change
• Background supporting product- and customer-focused research and feature development
• Proven open‑source research skills and experience supporting product development pipelines
• Familiarity with Python, Jira, Git, and related analytical or engineering collaboration tools
• Embodies a hungry, humble, and smart mindset: always learning, collaborating, and executing
• Ability to thrive in fast‑paced, cross-disciplinary environments with shifting priorities

Bonus Points For

• Experience operationalizing academic or technical models within private-sector or applied environments
• Ability to optimize resources and execute under tight deadlines
• Ability to communicate effectively with diverse internal and external audiences, including technical experts, customers, and business stakeholders
• Experience applying quantitative climatological models to supply chain risk at both local and global scales
• Strong verbal and written communication skills and comfort multi‑tasking in dynamic environments

What We Offer

• 401(k) with employer match
• Flexible Time Off (FTO) + 10 paid holidays
• Career growth opportunities and the ability 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

Compensation

Base Salary Range: $150,000 – $180,000 USD (depending on experience and location)
Variable Compensation: Performance-based annual bonus
Equity: Stock options included as part of the total compensation package
We believe in rewarding great work with competitive, transparent compensation. Final offers are based on skills, experience, and geographic location.

Work Environment, Location & Travel

This is a remote‑first role open to candidates legally authorized to work in the United States. This position may require travel.

Equal Opportunity Employer

interos.ai is proud to be an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees — regardless of race, religion, gender identity, sexual orientation, age, disability, or veteran status.

Accessibility & Accommodations

We are committed to providing reasonable accommodations for candidates throughout the hiring process. If you need assistance, please contact us at [e-mail].