Computational Geoscientist

Company Description

We are an early-stage, venture-backed startup at the intersection of AI and Critical Minerals exploration. Our core product is an end-to-end agentic platform that automates the identification and detailed interpretation of potential subsurface mineral deposits.

Role Description

We're looking for a Senior Computational Geoscientist to own the resource and prospectivity modeling layer of Octavia — the part of the system that turns raw interpretation outputs into where the minerals actually are, how much of it there is, and where to drill next. You'll sit between our geophysical analysis, ML research, and engineering teams, translating geological judgment into reproducible, code-driven models that the agent can run autonomously and that we can defend to exploration geologists and investors. This is a hands-on role for someone who is equally comfortable reasoning about mineralization zones as they are writing the Python that models them.

What you will do

• Build prospectivity and mineralization-zone models that fuse data from seismic, resistivity/EM, host-rock properties from well logs, and structural traps from fault detection into spatial predictions of where minerals are most likely concentrated.
• Own resource estimation — design and implement geostatistical workflows (variography, kriging/simulation, grade–tonnage modeling, uncertainty quantification) that produce auditable resource estimates from sparse and heterogeneous data.
• Construct 3D geological models and define the geological logic that grounds the AI agent's reasoning (stratigraphy, structural controls, depositional setting).
• Encode domain expertise into the system — work with the AI team to translate exploration heuristics and mineral-system models into the agent's geological ontology and reasoning rules.
• Validate model outputs against real datasets and known deposits, define what "good" looks like, and build the QA checks that keep the agent's geoscience honest.
• Work fluidly with multi-physics data — seismic (SEGY), well logs (LAS), GeoJSON geological layers, geological reports, and mineral-deposit databases.

What you bring

• Advanced degree (MSc or PhD) in geology, geophysics, geostatistics, or a closely related earth-science field.
• 5–10+ years applying quantitative methods to exploration or resource modeling
• Hands-on resource estimation and geostatistics experience — variography, kriging, conditional simulation, grade and tonnage estimation, and uncertainty.