Data Scientist – Staff or Senior

🕒 April 1

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KoBold Metals

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2019

🤖 Artificial Intelligence

🔬 Science

⚡ Energy

Artificial Intelligence • Science • Energy

KoBold Metals is a company specializing in advanced mineral exploration. By investing over $100 million annually across 60+ projects on five continents, KoBold is at the forefront of using artificial intelligence and novel hardware to transform mineral exploration into a repeatable science. The company aggregates comprehensive data on the Earth's crust and utilizes proprietary AI tools, including the Machine Prospector® system, to minimize uncertainties in exploration. KoBold Metals is committed to ethical exploration practices and is backed by world-class investors dedicated to discovering and developing new battery metal resources. Their innovative approach leverages AI to build the world's largest geoscience information collection and model subsurface data statistically.

📋 Description

• 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 our targeting efforts and inform our acquisition and exploration decisions. • Present to and collaborate with our external partners and stakeholders.

🎯 Requirements

• 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. • Technical skills, including 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.

🏖️ Benefits

• 401(k) matching