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Company

KoBold Metals · 1 day ago

Principal Data Scientist

United States

Full-time

Remote

Senior Level, Lead/Staff

$225K/yr - $265K/yr

10+ years exp

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Responsibilities

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.

Qualification

Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.

PythonCollaborative software developmentSQLPredictive modelingMachine LearningCloud computingApplied statisticsGeospatial analysesData visualizationImage processingGeostatisticsDistributed computingContainerization solutions

Required

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.

SQL, as well as familiarity with non-relational databases.

Cloud computing resources.

Building a wide variety of predictive models, applying them to different problems, and evaluating and interpreting the results.

Working with a broad range of types of data including data from physical systems.

Geospatial analyses and visualizations.

Broad skills in and knowledge of applied statistics.

Substantial understanding of Machine Learning algorithms.

An advanced degree in the 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.

Demonstrated ability to quickly absorb and synthesize complex information, with a track record of high intellectual rigor in a professional setting.

Exceptional curiosity and eagerness to learn, with a proactive approach to exploring new concepts and technologies.

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.