Principal Data Scientist

The job overview for the position of Staff Data Scientist at KoBold Metals is to contribute to the company's mission of using AI to explore for metals needed for the transition to a low-carbon economy. The role involves building predictive models and applying scientific computing methods to identify evidence of ore-forming processes and predict locations of ore-grade mineralization. The data scientist will work closely with geoscientists to incorporate their understanding of chemical and physical processes, create geologic predictions, design field programs, and reduce uncertainty in predictions. The goal is to make valuable discoveries by building data tools and contributing to the development of proprietary software exploration tools.

• Help develop KoBold’s proprietary software exploration tools.
• Find and curate a wide variety of geospectral, 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 a range of 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.

• Extensive experience with Python's data science packages and general software engineering practices
• Collaborative software development skills (git) and familiarity with software engineering best practices like unit testing

• Competitive salary range of $225,000 - $265,000
• Opportunity to work with a wide variety of geospectral, geophysical, geochemical, geologic, and geographic data
• Integration of data into KoBold's proprietary data system
• Building models to make statistically valid predictions about compositional anomalies within the Earth's crust
• Creating effective visualizations for evaluating model performance and interacting with data
• Applying data processing, statistical, and physics-based techniques to geoscientific data
• Collaboration with external partners and stakeholders
• Extensive experience with Python's data science packages and general software engineering practices
• Familiarity with collaborative software development, software engineering best practices, and CICD pipelines
• Knowledge of SQL and non-relational databases
• Experience with cloud computing resources
• Ability to work with a broad range of data types, including data from physical systems
• Skills in geospatial analyses and visualizations
• Broad skills in applied statistics and substantial understanding of Machine Learning algorithms
• Advanced degree in physical sciences, engineering, computer science, or mathematics
• 10 years of post-degree work experience as a data scientist or data engineer
• Ability to take ownership and responsibility of large projects
• Constant learning and driving insights and innovations
• Ability to collaborate with domain experts who aren't software developers
• Excitement about joining a fast-growing early-stage company and eagerness to take on a range of responsibilities
• Ability to independently prioritize multiple tasks effectively
• Optional experience with creating machine learning models on geospatial data, geostatistics, image processing or computer vision, distributed computing applications, and containerization solutions