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Climate Research Scientist Machine Learning Jobs

MIT Human Resources

Research Scientist 3

Cambridge, MA · On-site

... science, machine learning, use of machine learning for enhancing mathematical discovery and formal verification; help set the project's research direction, lead several of the program's parallel ...

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$50.5K

$130.1K

$174K

How much do climate research scientist machine learning jobs pay per year?

As of Aug 19, 2026, the average yearly pay for climate research scientist machine learning in the United States is $130,117.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,500.00 and $173,000.00 per year, depending on experience, location, and employer.

What does a climate research scientist specializing in machine learning do?

A Climate Research Scientist who specializes in Machine Learning uses advanced algorithms and computational models to analyze climate data and improve predictions about climate change. They work with large datasets from satellites, weather stations, and simulations to identify patterns, make forecasts, and assess environmental impacts. Their work helps inform policy decisions, guide mitigation strategies, and advance our scientific understanding of the Earth's climate system. Collaboration with other scientists, governments, and organizations is often a key part of the role.

What are the key skills and qualifications needed to thrive as a climate research scientist specializing in machine learning?

To thrive as a Climate Research Scientist specializing in Machine Learning, you need a solid background in climate science, statistical analysis, and advanced machine learning techniques, typically supported by a graduate degree in a related field. Experience with programming languages like Python or R, familiarity with climate modeling software, and proficiency in machine learning frameworks such as TensorFlow or PyTorch are highly valuable. Strong analytical thinking, problem-solving abilities, and effective communication skills help you explain complex findings to diverse audiences and collaborate across disciplines. These skills and qualities are crucial for advancing climate research, developing innovative solutions, and informing policy decisions based on robust data analysis.

How do climate research scientists specializing in machine learning typically collaborate with multidisciplinary teams?

Climate Research Scientists with expertise in Machine Learning often work closely with meteorologists, data engineers, environmental scientists, and policy experts. They contribute by developing and refining predictive models using large climate datasets, while also translating complex outputs into actionable insights for decision-makers. Collaboration often involves regular team meetings, joint publications, and integrating domain expertise to ensure that the models are both scientifically robust and practically useful. Strong communication skills are valuable, as these scientists frequently explain technical concepts to colleagues from non-technical backgrounds.

What is the difference between Climate Research Scientist Machine Learning vs Climate Data Analyst?

AspectClimate Research Scientist Machine LearningClimate Data Analyst
Required CredentialsMaster's or PhD in Climate Science, Data Science, or related fields; knowledge of machine learningBachelor's or Master's in Environmental Science, Data Analysis, or related fields; proficiency in data tools
Work EnvironmentResearch labs, universities, environmental agencies, often collaborative and interdisciplinaryGovernment agencies, consulting firms, NGOs; focus on data processing and reporting
Employer & Industry UsageResearch institutions, academia, environmental organizations integrating machine learningPolicy organizations, environmental consultancies analyzing climate data

While both roles involve climate data, Climate Research Scientist Machine Learning focuses on developing predictive models using advanced algorithms, whereas Climate Data Analysts primarily process and interpret climate datasets to inform decisions. The former requires more specialized knowledge in machine learning techniques, while the latter emphasizes data management and reporting skills.

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What cities are hiring for Climate Research Scientist Machine Learning jobs?

Cities with the most Climate Research Scientist Machine Learning job openings:

What states have the most Climate Research Scientist Machine Learning jobs?

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Climate Research Scientist Machine Learning jobs near you
Infographic showing various Climate Research Scientist Machine Learning job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 23% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $130,117 per year, or $62.6 per hour.

Lead Research Scientist - Machine Learning (Clearance Required)

STR

Woburn, MA • On-site

Full-time

Re-posted 15 days ago

Job description

Job Summary:
STR is a technology company specializing in advanced research and development for defense, intelligence, and national security. As a Lead Research Scientist, you will develop AI/ML algorithms for signals exploitation and system resource management, leading project teams and interacting with customers to solve high-impact problems.
Responsibilities:
• Help develop disruptive technologies focused on signals exploitation, estimation theory, system resource management, and systems analysis.
• Lead the development of cutting-edge AI/ML algorithms for novel application domains and modalities.
• Participate on and lead project teams, and interact with customers.
• Explore fascinating datasets, develop cutting-edge algorithmic techniques, and solve high-impact, unique problems for our customers.
Qualifications:
Required:
• Active Top Secret Clearance Required with SCI eligibility, for which U.S citizenship is needed by the U.S government
• MS with at least 8 years of experience, and/or PhD with at least 5 years of experience (or equivalent experience) in a scientific field such as applied math, physics, electrical engineering, computer science, or data science
• Experience building neural networks using standard deep learning tools (e.g., PyTorch, JAX, TensorFlow), including implementing new layers/network architectures, model training, hyperparameter tuning, and ablation studies
• Experience adapting novel machine learning approaches (e.g., from academic literature) to new data sets and problems
• Experience with standard data science tools such as scikit-learn, Pandas, and Matplotlib
• Proficiency in one or more programming languages: Python, C/C++
• Able to work, collaborate on, and lead multi-disciplinary teams
• Able to communicate technical foundations of models and algorithms to technical and non-technical audiences
• Experience in intelligence or military-related mission areas
Preferred:
• Experience applying deep learning to domains other than images/text, such as time series, discrete event sequence, or geospatial
• Experience with self-supervised machine learning
• Expertise working with time series, geospatial, and/or spatio-temporal data
Company:
STR is built on people & technology platforms tackling tough problems in cybersecurity, distributed sensing & artificial. Founded in 2010, the company is headquartered in Woburn, USA, with a team of 501-1000 employees. The company is currently Late Stage.

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