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Climate Modelling Jobs (NOW HIRING)

Oxman

Computational Ecologist

New York, NY · On-site

$152K - $241K/yr

... and climate-resilient developments. Together with our clients, we are designing biodiverse ... Leading of the modelling of core ecosystem dynamics and interactions as defined in the ...

Arup

Graduate Mechanical Engineer

Los Angeles, CA · On-site

... clients, climate and communities. The Opportunity * Design of Heating, Ventilation and Air ... Perform engineering analysis and modelling, including whole building load calculations and energy ...

isone

Data Scientist

Kinston, NC · Hybrid

$117K - $146K/yr

... modelling in the energy sector * Knowledge about distributed energy resources (e.g. photovoltaics, batteries), electric vehicles, and/or cold-climate heat pumps This employer will not sponsor ...

Carrier

Systems Engineer

Charlotte, NC · On-site

$64K - $129K/yr

Through cutting-edge advancements in climate solutions such as temperature control, air quality and ... Thermodynamic based modelling and optimization of chiller system design. * Execute tests for ...

Carrier

Systems Engineer

Charlotte, NC · Hybrid

$64K - $129K/yr

Through cutting-edge advancements in climate solutions such as temperature control, air quality and ... Thermodynamic based modelling and optimization of chiller system design. * Execute tests for ...

ISO New England, Inc.

Data Scientist

Windsor, CT · On-site

$117K - $146K/yr

... modelling in the energy sector * Knowledge about distributed energy resources (e.g. photovoltaics, batteries), electric vehicles, and/or cold-climate heat pumps This employer will not sponsor ...

HSBC

AVP, Financial Engineering

Manhattan, NY · On-site

Support modelling in delivering these models within our software engineering best practice ... and Climate Change Initiatives. You'll want to join our Employee Resource Groups as they play a ...

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Climate Modelling information

What is climate modelling?

Climate modelling is the use of computer-based mathematical models to simulate the Earth's climate system, including the atmosphere, oceans, land surface, and ice. These models help scientists understand past, present, and future climate conditions by analyzing interactions between various components of the climate. Climate models are essential tools for predicting future climate changes, assessing the impact of human activities, and informing policy decisions related to climate change mitigation and adaptation.

What are some typical collaborative projects that climate modellers work on with other scientists?

Climate modellers frequently collaborate with meteorologists, oceanographers, data scientists, and policy experts to create comprehensive simulations and forecasts. These joint projects might include developing regional climate impact assessments, evaluating mitigation strategies, or contributing to international reports like those from the IPCC. Working in interdisciplinary teams allows climate modellers to integrate diverse data sets and perspectives, enhancing the accuracy and relevance of their models. Collaboration is essential for translating complex climate data into actionable insights for stakeholders and policymakers.

What are the key skills and qualifications needed to thrive as a Climate Modeller, and why are they important?

To thrive as a Climate Modeller, you need a strong background in atmospheric sciences, mathematics, and programming, typically supported by an advanced degree in climate science, meteorology, or a related field. Proficiency with climate modelling software (such as WRF or CESM), data analysis tools (like Python, MATLAB, or R), and experience with high-performance computing environments are essential. Strong analytical thinking, problem-solving abilities, and effective communication skills help translate complex model outputs into actionable insights. These skills and qualities are crucial for producing accurate climate projections that inform policy decisions and scientific understanding.

What is the difference between Climate Modelling vs Climate Data Analysis?

AspectClimate ModellingClimate Data Analysis
Required CredentialsBachelor's or Master's in Environmental Science, Meteorology, or related fields; programming skillsBachelor's or Master's in Data Science, Statistics, or related fields; strong analytical skills
Work EnvironmentResearch labs, universities, government agencies; computational and simulation workData centers, research institutions, consulting firms; data processing and interpretation
Employer & Industry UsageClimate research, environmental agencies, academiaEnvironmental consulting, research, policy analysis

Climate Modelling involves creating simulations to predict climate patterns using complex models, while Climate Data Analysis focuses on interpreting existing climate data to identify trends and insights. Both roles require strong analytical skills but differ in their approach—modeling emphasizes simulation, whereas data analysis emphasizes data interpretation.

More about Climate Modelling jobs
What cities are hiring for Climate Modelling jobs? Cities with the most Climate Modelling job openings:
What states have the most Climate Modelling jobs? States with the most job openings for Climate Modelling jobs include:
What job categories do people searching Climate Modelling jobs look for? The top searched job categories for Climate Modelling jobs are:
Climate Modelling jobs near you
Infographic showing various Climate Modelling job openings in the United States as of June 2026, with employment types broken down into 85% Full Time, and 15% Part Time. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution.
Computational Ecologist

Computational Ecologist

Oxman

New York, NY • On-site

$152K - $241K/yr

Full-time

Posted 18 days ago

Job description

OXMAN
OXMAN is a nature-based research and design company based in Manhattan. We incubate ventures and technologies that reimagine the relationship between humanity and the natural world. Working across disciplines-from architecture and ecology to materials science and computation, we develop nature-centric solutions to critical environmental challenges.
EDEN
Nature provides humanity with services that are critical for survival: the sequestration of carbon, the filtration of water, and the production of the air we breathe. EDEN works to strengthen and regenerate these natural processes by cultivating biodiverse, resilient ecosystems that sustain life for all species-human and non-human alike.
EDEN is a digital design environment for engineering and designing ecosystems, modeling the flows, relationships, and processes that sustain them. We build tools that quantify how landscapes can be engineered to achieve specific performance goals, cooling cities, filtering water, sequestering carbon, and protecting key species, and use them to guide the design of ecologically active sites.
One hectare of well-designed landscape can sequester up to four times the annual emissions of an average home, filter enough water to support thirteen neighborhoods, and reduce ambient temperatures by more than ten degrees. EDEN enables designers to plan intentionally for these outcomes through analysis, simulation, and optimization, turning ecological function into an actionable design parameter.
Our design team works directly with clients to apply these tools toward site-specific goals, from logistics campuses and residential communities to rewilding and climate-resilient developments. Together with our clients, we are designing biodiverse, productive environments that serve both humanity and nature.
Key Responsibilities
  • Conceptualization and Research: Research and identify key ecosystem behaviours and interactions to create a comprehensive conceptual framework for general ecosystem modelling
  • Ecosystem Behaviour Modelling: Leading of the modelling of core ecosystem dynamics and interactions as defined in the conceptualization phase such as plant growth and succession etc.
  • Ecosystem Metrics Development: Development of quantitative metrics to assess ecosystem health, stability, and service provision.
  • Implementation and Documentation: Models will be implemented in a computationally efficient framework with thorough documentation to ensure usability and reproducibility.
  • Help in the gathering and integration of relevant environmental, ecological, and spatial data to underpin model parameters and validate model outcomes.
  • Conduct data analysis to in order to derive key insights necessary to develop ecosystem models and validate model parameters.
  • Technical documentation: Prepare comprehensive documentation outlining model assumptions, data sources, code structure, and operation for using and maintaining the models.
  • Continually communicate with the OXMAN team to ensure review of research, implementation, and seamless integration of the model into their workflows.
  • Participate in regular progress meetings (weekly or biweekly) with the team to review milestones, discuss challenges, and plan next steps.
  • Provide status updates summarizing progress, challenges encountered, and any adjustments to the project plan.
Key Goals and Outcomes
  • Development, deployment, and validation of a general ecosystem model within two quarters of the start date
Required Experience
  • A Ph.D. or equivalent experience in Computer Science, Computational Ecology, Systems Biology, or a related field.
  • Strong programming skills in languages such as Python, C++, or similar, with experience in frameworks like PyTorch, or JAX.
  • Strong foundation in modeling techniques (e.g., differential equations, agent-based modeling, network models, Bayesian approaches) for simulating ecological processes or population dynamics.
  • Experience handling large and often messy datasets common in ecology (e.g., climate data, remote sensing imagery, biodiversity records). Knowledge of spatial databases, parallel computing, or cloud-based data storage is a plus
Technical Skills
  • Python (NumPy/SciPy/pandas), reproducible research workflows, and Git-based version control
  • High-performance model implementation (vectorization, profiling/optimization); familiarity with PyTorch or JAX
  • Ecological modeling methods: agent-based, ODE/PDE, network, and Bayesian/statistical modeling; uncertainty quantification
  • Geospatial analytics (GIS; GeoPandas/rasterio/GDAL) and spatial databases (e.g., PostGIS) for integrating environmental and biodiversity data
  • Remote sensing and gridded data handling (e.g., xarray; land cover/land use change; climate rasters); comfort with messy real-world datasets
  • Clear technical documentation (assumptions, data provenance, APIs) and maintainable code (testing, modular design)
Essential Qualities
  • Systems-level thinker who can translate ecological theory into tractable computational abstractions
  • Strong research judgment: literature synthesis, hypothesis framing, and disciplined model validation
  • Pragmatic engineer: prioritizes computational efficiency, robustness, and reproducibility over "toy" prototypes
  • Comfortable working with uncertainty, noisy data, and incomplete ground truth, typical of ecological problems
  • Clear communicator in interdisciplinary teams (design, biology, engineering); proactive stakeholder management
  • High ownership: independently drives milestones while aligning work to EDEN workflow integration needs

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