Description:

The Principal Data Scientist will build predictive models and apply scientific computing, statistical, and physics-based methods to identify evidence of ore-forming processes and predict locations of ore-grade mineralization in 2D and 3D.
This role involves creating a worldwide dataset for the exploration program, focusing on identifying and quantifying uncertainty in data and predictions.
The candidate will develop software to accelerate the discovery of critical battery metals and work closely with geoscientists to incorporate knowledge of chemical and physical processes that create ore deposits.
Responsibilities include developing proprietary software exploration tools, curating various geospectral, geophysical, geochemical, geologic, and geographic data, and integrating it into KoBold’s data system.
The Principal Data Scientist will build models for statistically valid predictions about compositional anomalies in the Earth’s crust and create visualizations for model performance evaluation.
The role requires collaboration with external partners and stakeholders to present findings and insights.

Requirements:

Candidates must have extensive experience with Python’s data science packages and general software engineering practices.
Familiarity with collaborative software development (git) and software engineering best practices, including unit test/integration test suites and CICD pipelines, is required.
Proficiency in SQL and familiarity with non-relational databases is necessary.
Experience with cloud computing resources and building a variety of predictive models is essential.
Candidates should have a broad range of data experience, including data from physical systems, and be skilled in geospatial analyses and visualizations.
An advanced degree in physical sciences, engineering, computer science, or mathematics is required, along with 10 years of post-degree work experience as a data scientist or data engineer.
Candidates should demonstrate ownership of large projects, the ability to synthesize complex information, and a proactive approach to learning new concepts and technologies.
Experience with creating machine learning models on geospatial data, geostatistics, image processing, distributed computing applications, and containerization solutions is helpful but not required.

This position offers a competitive salary range of $225,000 - $265,000 for full-time exempt employees.
KoBold Metals is a remote-first workplace, allowing candidates to work from anywhere in the United States or Canada.
The company is committed to equal employment opportunities and provides an affirmative action workplace for individuals of diverse backgrounds.