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Employment type:
Full time
Experience required:
Intermediate
Salary
Salary not provided
About the company:
Data Scientist
We are seeking a highly skilled and analytically rigorous Data Scientist to join our team. This role involves tackling complex, large-scale data challenges using advanced quantitative methods, with a specific application domain focused on spatial data relevant to environmental systems. You will be responsible for designing, implementing, and deploying sophisticated statistical models, measurement frameworks, and data infrastructure that directly inform critical business and scientific decisions. This is an Individual Contributor (IC) role demanding significant technical depth, intellectual curiosity, and the ability to drive foundational advancements in our analytical capabilities.
Location: São Paulo, Brazil
Languages: English required, Portuguese a plus
Role Responsibilities:
Develop and productionize statistically rigorous measurement frameworks and experimental designs suitable for field deployment and robust estimation of carbon removals.
Develop, validate, and deploy advanced statistical and machine learning models leveraging complex spatial and temporal data for prediction, imputation, and inference.
Architect and manage data storage solutions optimized for performant storage and retrieval of national-scale spatial datasets.
Conduct cutting-edge research into novel spatial sampling methodologies and statistical inference techniques tailored to challenging real-world constraints, particularly within the context of ERW.
Collaborate closely with engineering teams to integrate quantitative models and data infrastructure into scalable systems and operational platforms.
Background and Requirements:
PhD in Statistics, Applied Mathematics, related quantitative field, or equivalent experience, with demonstrated expertise in developing model applications for real-world deployment, particularly in environmental contexts.
Strong mathematical foundation with proven ability to develop and validate robust statistical and machine learning models that leverage complex spatial-temporal data for prediction and inference.
Strong programming skills (Python preferred, but R/MATLAB/Julia/C/Java/etc is fine), with experience building efficient data pipelines and working in a shared codebase.
Exceptional communication and collaboration skills with proven ability to work across multidisciplinary teams (engineering, science, commercial) to translate complex technical concepts and drive measurable impact for stakeholders.
Nice to Haves:
Familiarity with Julia for high-performance numerical computing.
Experience in agriculture, environmental science, climate tech, or remote sensing.
Experience working with large-scale environmental data, remote sensing data, or public gridded datasets.
Experience with building data pipelines and API integrations.
Personal Attributes:
Strategic thinker who can balance short-term needs with long-term vision.
Highly collaborative, with strong leadership skills and a hands-on approach to problem-solving.
Ability to navigate ambiguity and prioritize effectively in a fast-paced environment.
A positive, action-oriented mindset with a focus on outcomes.
Strong communication skills to convey complex quantitative concepts to diverse audiences.
What does success look like in this role?
Driving significant advancements in our core quantitative methodologies and technical infrastructure, directly enabling more accurate carbon removals measurement, robust verification, and effective decision-making for our scientific and operational teams.
About Terradot:
Our mission is to stabilize Earth’s climate by transforming nature’s most powerful permanent carbon removal process into a global climate solution. By advancing science, building technology, and assembling a global coalition, we are catalyzing a global initiative to scale Enhanced Rock Weathering within the next decade, starting in Brazil.
Founded out of the Stanford University ecosystem, Terradot is led by the world’s leading experts to advance the science and technology of ERW. Our unique structure bridges industry, academia, and government and allows our team to contribute with speed & scale. We have raised $58.2M in total funding from John Doerr, Sheryl Sandberg & Tom Bernthal, George Roberts, Microsoft’s Climate Innovation Fund, Google, Cisco and Venture Funds, Floodgate, Kleiner Perkins, Acre Venture Partners, Gigascale Capital, Valor Capital, Ponderosa Ventures and others. We have sold ~300,000 tons in offtakes from leading CDR buyers like Frontier and Google.
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status, or any other characteristic protected by law. 1 Research suggests that qualified people from historically marginalized groups may self-select out of opportunities if they don't meet 100% of the job requirements. We encourage individuals who believe they have the skills necessary to thrive to apply for this role.
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