Applied Scientist
New
K
KoBold MetalsMineral Exploration
Candidates can be located anywhere in the United States or Canada.Full-Time
Salary$125,000 and $235,000
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Job Details
- Required Skills
- PythonSQLCloud ComputingData AnalysisGitMachine Learning
Requirements
- Exceptional curiosity, eagerness to learn, and ability to synthesize complex information.
- Demonstrated track record of developing complex equipment with cross-disciplinary teams and vendors.
- Extensive experience with physical measurement and data analysis systems involving optics, electromagnetism, radiation, or gravity.
- Proficiency in Python data science packages and software engineering best practices.
- Experience with collaborative software development (git) and CI/CD pipelines.
- Strong knowledge of SQL and familiarity with non-relational databases.
- Experience with cloud computing resources.
- Ability to build, evaluate, and interpret predictive models using broad data types.
- Experience applying data analysis, physics, and applied statistics to data from physical systems.
- Experience deploying sensors in the field.
- Ability to work with noisy, disparate data and solve challenges in applying ML to mineral exploration.
- Must be able to travel 10-20% of the time.
Responsibilities
- Design, develop, and deploy new mineral exploration data collection instruments and methods.
- 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 and use the results to guide targeting efforts.
- Present to and collaborate with external partners and stakeholders.
- Push the state of the art in analysis capabilities by implementing statistically rigorous spatially aware clustering, anomaly detection, and other analysis methods.
- Collaborate with data scientists, geoscientists and engineers to invent and deploy algorithms that combine large and complex data sets for mineral exploration and discoveries.
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