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Climate Research Scientist Machine Learning Jobs

ISEE

Research Scientist - Machine Learning

... Conducting research in the areas of: Robotics, Artificial Intelligence, Machine Learning ... in Robotics, Computer Science, Electrical Engineering, Aerospace Engineering, Mechanical ...

STR

Lead Research Scientist - Machine Learning

Woburn, MA

$174K - $220K/yr

... machine learning, statistics, estimation theory, and information theory algorithms for signals ... The Role As a Lead Research Scientist at STR, you will help develop disruptive technologies focused ...

STR

Lead Research Scientist - Machine Learning

Woburn, MA · On-site

$174K - $220K/yr

... machine learning, statistics, estimation theory, and information theory algorithms for signals ... The Role As a Lead Research Scientist at STR, you will help develop disruptive technologies focused ...

STR

Lead Research Scientist - Machine Learning

Boston, MA

$174K - $220K/yr

... machine learning, statistics, estimation theory, and information theory algorithms for signals ... The Role As a Lead Research Scientist at STR, you will help develop disruptive technologies focused ...

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Climate Research Scientist Machine Learning information

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$50.5K

$130.1K

$174K

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

As of Jul 29, 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 are the key skills and qualifications needed to thrive as a Climate Research Scientist specializing in Machine Learning, and why are they important?

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.

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.

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.

More about Climate Research Scientist Machine Learning jobs
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? States with the most job openings for Climate Research Scientist Machine Learning jobs include:
What job categories do people searching Climate Research Scientist Machine Learning jobs look for? The top searched job categories for Climate Research Scientist Machine Learning jobs are:
Climate Research Scientist Machine Learning jobs near you
Infographic showing various Climate Research Scientist Machine Learning job openings in the United States as of July 2026, with employment types broken down into 81% Full Time, 16% Part Time, 1% Temporary, 1% Contract, and 1% Nights. Highlights an 95% Physical, 1% Hybrid, and 4% Remote job distribution, with an average salary of $130,117 per year, or $62.6 per hour.

Senior Research Scientist, Machine Learning

Analogdevices

Boston, MA

$170K - $216K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 21 days ago

Job description

About Analog Devices

Analog Devices, Inc. (NASDAQ:ADI) is a global semiconductor leader that bridges the physical and digital worlds to enable breakthroughs at the Intelligent Edge. ADI combines analog, digital, and software technologies into solutions that help drive advancements in digitized factories, mobility, and digital healthcare, combat climate change, and reliably connect humans and the world. With revenue of more than $9 billion in FY24 and approximately 24,000 people globally, ADI ensures today's innovators stay Ahead of What's Possible. Learn more atwww.analog.comand onLinkedInandTwitter (X).

Employer: Analog Devices, Inc.

Job Title: Senior Research Scientist, Machine Learning

Job Requisition: 1010.292.5 / R262485

Job Location: Boston, Massachusetts

Job Type: Full Time

Rate of Pay:$170,445 - $216,000 per year

Duties: Design, implement, and optimize novel Machine Learning ("ML") algorithms specialized for applications, such as energy, healthcare, and robotics. Develop software simulations and analyze the performance of algorithms across various simulated and real-world datasets and hardware-constrained environments. Help with prototyping systems, algorithms, and methods to prove and validate their performance and practicality. Work with other researchers and engineers, inside and outside the Algorithmic Solutions Group, to connect our work with our mission statement. Stay abreast of state-of-the-art algorithms and research advances beyond the state of the art in areas relevant to Analog Devices.

Partial telecommute benefit (up to 2 days/week work from home).

Requirements: Must have a Master's degree in Computer and Information Technology, Computer Science, Computer Engg, Electrical Engg, or closely related technical discipline (willing to accept foreign education equivalent) and two (2) years of experience in the job proffered or related occupation conducting machine learning (ML) research and development in Energy, Security, Communication, or Healthcare.

Must also possess the following (quantitative experience requirements not applicable to this section):

  • Demonstrated Expertise ("DE") in machine learning ("ML") algorithm development and deployment of end-to-end ML pipelines using at least one of the following frameworks: Tensorflow, Keras, Pytorch, Caffe, or Jax;
  • DE developing and applying neural networks, deep learning, transformers, and Large Language ML models; and
  • DE with algorithm prototyping, simulation, and high-quality software engineering using Python and C/C++.

Contact: Eligible for employee referral program. Apply online at https://www.analog.com/en/careers.html and Reference Position Number: R262485.

For positions requiring access to technical data, Analog Devices, Inc. may have to obtain export licensing approval from the U.S. Department of Commerce - Bureau of Industry and Security and/or the U.S. Department of State - Directorate of Defense Trade Controls. As such, applicants for this position - except US Citizens, US Permanent Residents, and protected individuals as defined by 8 U.S.C. 1324b(a)(3) - may have to go through an export licensing review process.

Analog Devices is an equal opportunity employer. We foster a culture where everyone has an opportunity to succeed regardless of their race, color, religion, age, ancestry, national origin, social or ethnic origin, sex, sexual orientation, gender, gender identity, gender expression, marital status, pregnancy, parental status, disability, medical condition, genetic information, military or veteran status, union membership, and political affiliation, or any other legally protected group.

EEO is the Law: Notice of Applicant Rights Under the Law.

Job Req Type: ExperiencedRequired Travel: NoShift Type: 1st Shift/Days

  • Actual wage offered may vary depending on work location, experience, education, training, external market data, internal pay equity, or other bona fide factors.

  • This position qualifies for a discretionary performance-based bonus which is based on personal and company factors.

  • This position includes medical, vision and dental coverage, 401k, paid vacation, holidays, and sick time, and other benefits.

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