Climate Data Scientist
About Climate Central:
Climate Central is an independent group of scientists and science translators who research and report the facts about our changing climate and how it affects people’s lives. We use science and tech to generate thousands of local storylines and compelling visuals that make climate change relevant and show what can be done about it. We address climate science, sea level rise, extreme weather, energy, and related topics. We collaborate with journalists, TV meteorologists, and other respected messengers, reaching broad audiences through local voices in the US and 150 nations. Our research and visuals appear in thousands of TV spots and well over ten thousand other news stories each year, and our impact is growing.
About the role:
Climate Central is seeking a highly-skilled Climate Data Scientist to join our team. Reporting to the Vice President for Science, the scientist will be part of a new initiative in climate services to deliver actionable and interpretable probabilistic predictions of climate hazards on seasonal-to-decadal timescales. This initiative will build on Climate Central’s existing multi-method daily, high-resolution estimates of how strongly climate change is influencing conditions in the atmosphere and ocean. The scientist will work quickly and creatively to research, develop, and deliver new statistical analyses and decision-ready products that meet cross-sector needs for climate risk and hazard planning.
The ideal candidate will have a foundational working knowledge of climate science and modeling as well as experience developing data-driven methods for prediction problems. This position is for a two-year term with the possibility of renewal.
Key Responsibilities
Area #1: Assessing and developing annual to decadal prediction methods
Carrying out literature reviews of existing methodologies and datasets
Identifying gaps in existing 1-to-10 year prediction products
Developing multi-method approaches that result in unique Climate Central product offerings
Area #2: Advancing the science
Using climate models and data to develop and validate predictions of natural hazards or perils in the 1-to-10 year window
Developing scientifically sound technical reports that clearly convey data uncertainties and methodological details to build trust in forecast products developed for end users
Presenting results at scientific conferences
Area #3: Translating research into decision-ready products
Developing statistical models that predict local climate risks and collaborating with technical staff to turn these into operational service products
Working with our technical, engagement, and business development teams to create forecast products that meet end-user needs
Working with our communications team to ensure products are accurately and accessibly reflected in externally facing materials
Other duties may be assigned as needed.
Required Skills and Experience:
This position requires an advanced degree in a relevant field and experience applying data-driven statistical approaches to climate model outputs
Experience with rigorous model evaluation, uncertainty, and validation techniques for probabilistic statistical modeling
Experience analyzing and visualizing large climate and geospatial datasets in Python using packages such as Xarray, pandas, statsmodels, and scikit-learn
Ability to work collaboratively within a fast-paced environment and to see perspectives across different disciplines and vocabularies
Excellent communications skills with a track record of effectively communicating about data and scientific findings
Preferred Qualifications:
Experience working for a federal agency or lab that has been impacted by recent cuts
Comfort in working in GitHub and with parallel and distributed computing tools to turn complex big data projects into efficient analysis pipelines (e.g., Dask, Zarr, multiprocessing, joblib, and high-performance computing or cloud workflows) and end-user-ready products
Experience working with seasonal-to-decadal forecasting models and/or large ensembles
Familiarity with novel AI and/or supervised and unsupervised machine learning techniques, including using Python packages such as PyTorch, TensorFlow/Keras, or XGBoost
Familiarity with the science and/or data relevant to quantifying climate risk in one or more sectors, such as health or economics
Experience in working with statistical and/or dynamical downscaling techniques and bias-adjustment for producing fine-scale resolution information
Experience producing scientific manuscripts and reports
Compensation: The expected base salary range for this position is $85,000-$92,000. Within the range, individual pay is determined by job-related skills, experience, and relevant education or training. Climate Central offers generous benefits including:
Medical benefits
Dental/ Vision benefits
More than 7 weeks of paid vacation and holidays available annually
12 weeks of paid family leave
401k with up to 12% matching
Partial college tuition for children of employees who qualify
Location and employment eligibility:
This position will be remote, in accordance with Climate Central organizational policy. Presence at headquarters or other U.S.-based locations is required for periodic team and organizational meetings, events and convenings. Climate Central’s headquarters are in Princeton, N.J. Candidates must be eligible for employment in the United States.
Equity and EEO language: Climate Central is an Equal Employment Opportunity employer and promotes a diverse and inclusive workplace. We do not discriminate against any applicant for employment or employee on the basis of race, color, religious creed, gender, age, marital status, sexual orientation, national origin, disability, veteran status or any other classification protected by applicable discrimination laws.
How To Apply: Please apply via this link. The application deadline is February 9, 2026 at 5pm ET.
Please note that our application process requires the submission of a resume only. We are intentionally not asking for a cover letter, so please do not send one with your application.
When including your education history in your resume, please remove the name of your school from your resume. You may leave your degree (e.g., “B.A. Communication”), but please remove any undergraduate or graduate school names. This is one part of our effort to assess candidates against the required skills and experience for this role and to mitigate bias in the decision making process.
Due to the volume of employment applications and queries received, Climate Central is unable to respond to each application individually. Applicants will be contacted directly if selected as a candidate.