Quantitative Research Associate

Job Title : Quantitative Research Associate

Location:

Team:

Experience:

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About Alt Carbon:

Alt Carbon was started by sibling tea planters Shrey and Sparsh Agarwal, in order to rescue their familys tea estate from being at-risk of climate impact to becoming the frontier of climate action.

Read about our journey below:

Our Journey to Revive Darjeeling

To read more about our work, check out this news feature about us, go through this twitter thread, or have a look at our work in Darjeeling.

About the Role

Alt Carbon is building a new generation of scientific infrastructure to support high-integrity Carbon Dioxide Removal (CDR) through Enhanced Rock Weathering (ERW). At the heart of this effort is a robust, quantitative approach to modeling weathering reactions, tracking elemental fluxes, and calculating real-world net CO? removal.

Quantitative Research Associate

Key Responsibilities

• Design and validate

  mathematical models

  of mineral weathering, geochemical fluxes, and carbon sequestration
• Conduct

  uncertainty quantification

  and

  error propagation analysis

  across sampling and modeling workflows
• Build

  Monte Carlo simulations

  and other stochastic models for registry-aligned carbon accounting
• Analyze datasets from lab, field, and satellite sources to extract meaningful patterns and trends
• Support the development of

  sampling strategies

  , including spatial and temporal optimization
• Collaborate with product and software teams to embed scientific logic into automated MRV platforms
• Contribute to whitepapers, publications, and technical memos for third-party validation

Qualifications

• Bachelor&aposs or Masters degree in:

Mathematics / Applied Statistics / Data Science

Physics / Environmental Engineering / Computational Sciences

Or equivalent with strong quantitative background

• Experience with:

Statistical modeling and inference

Error analysis, confidence intervals, and sensitivity testing

Simulation methods

• Proficiency in Python (preferred) or R for modeling and data analysis
• Comfort with reading scientific papers and replicating models/equations
• Bonus: Experience with spatial data, environmental datasets, or climate modeling
• Bonus: Understanding of basic geochemical or environmental systems (not required can learn on the job)

Who You Are

• Youre a quantitative thinker who gets excited by real-world complexity
• You treat uncertainty not as a nuisance, but as a solvable scientific problem
• Youre comfortable toggling between equations, field data, and code
• Youre rigorous with numbers, but open-minded to scientific intuition
• You want your models to matter in public policy, climate impact, and planetary systems

Why This Matters

soil, rock, rain, and real-world data