Data Scientist
Job description
Data Scientist building predictive models and scientific computing tools to locate ore-grade mineral deposits for an AI-native mineral exploration company. The role involves creating 2D and 3D geologic predictions, curating geoscientific data, and working closely with geoscientists to guide exploration.
At a glance
- Employment
- Full-time · Employee (employment agreement)
- Work mode
- Remote
- Pay
- USD 140,000 – 260,000 / year
What you'll do
- Help develop KoBold's proprietary software exploration tools
- Find and curate geophysical, geochemical, geologic, and geographic data and integrate it into KoBold's proprietary data system
- Build models to make statistically valid predictions about the locations of compositional anomalies within the Earth's crust
- Create effective visualizations for evaluating model performance and enabling rapid interaction with the underlying data and key features
- Develop and apply data processing, statistical, and physics-based techniques to geoscientific data — from computer vision to geophysical inversions — and use the results to guide targeting efforts and inform acquisition and exploration decisions
- Present to and collaborate with external partners and stakeholders
What we're looking for
- Extensive experience with Python's data science packages and general software engineering practices
- Collaborative software development (git), and familiarity with software engineering best practices like unit test / integration test suites, and CICD pipelines
- Cloud computing resources
- Building predictive models, applying them to different problems, and evaluating and interpreting the results
- Data from a variety of physical systems
- Geospatial analyses and visualizations
- Broad skills in and knowledge of applied statistics and Bayesian inference
- Substantial understanding of machine learning algorithms
- An advanced degree in the physical sciences, engineering, computer science, or mathematics
- A minimum work experience of 4 years post PhD or 8 years post MS, ideally as a data scientist or data engineer
- Experience leading technical teams to apply novel scientific approaches to core business problems
- Ability to take ownership and responsibility of large projects
- Ability to explain technical problems to and collaborate on solutions with domain experts
- Communicates well on a collaborative, cross-functional team
- Excitement about joining a fast-growing early-stage company, comfort with a dynamic work environment, and eagerness to take on a range of responsibilities
- Ability to independently prioritize multiple tasks effectively
- Intellectual curiosity and eagerness to learn about all aspects of mineral exploration, particularly in the geology domain
- Enjoys constantly learning such that you are driving insights through using our tools in exploration and willing to work directly with geologists in the field
- Keen not just to build cool technology, but to figure out what technical product to build to best achieve the business objectives of the company
- A valid passport and willingness to travel to observe our work at Mingomba or at an exploration site around the world
Nice to have
- Creating machine learning models on geospatial data
- Geostatistics
- Image processing or computer vision
- Distributed computing applications for machine learning and other computations
Benefits
- Equity
- Benefits including 401k match
Apply
About KoBold Metals
The first AI native mineral exploration, mine development, and technology development company
KoBold Metals integrates artificial intelligence, human intelligence, and new technology to discover critical minerals such as copper, lithium, and cobalt. Its multidisciplinary teams of data scientists, engineers, and geologists build data systems, design new sensors, and establish industry-leading workflows to develop and test subsurface predictions on exploration projects. Its first discovery, Mingomba, is a high-grade copper deposit in Zambia.
Mission
To turn mineral exploration into a repeatable science to discover the minerals the world needs—by integrating artificial intelligence, human intelligence, and new technology.
Key facts
- Mineral exploration and mining
- First discovery, Mingomba, is a high-grade copper deposit in Zambia
- Runs exploration programs in eight countries
- Privately held
- Investors include T. Rowe Price, Canada Pension Plan Investments, Andreessen Horowitz, Breakthrough Energy Ventures, BOND Capital, Durable Capital, StepStone, Standard Investments, BHP, and Mitsubishi
Partners & customers