Applied Scientist

Summary

Join KoBold, a leading mineral exploration company, and contribute to developing cutting-edge instruments for data collection to guide exploration programs. You will design, build, and deploy hardware, working with vendors and operations staff. Using sensor data and other sources, you will build models applying scientific computing, statistical, and physics-based methods to predict ore locations. You will create a worldwide dataset, carefully addressing uncertainty. Collaborate with data scientists, engineers, and geoscientists to incorporate geological understanding and identify new opportunities. Help KoBold make valuable discoveries by building and deploying next-generation hardware and data tools, contributing to a fast-growing team.

Requirements

• 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
• A successful track record of developing complex equipment with cross-disciplinary teams and vendors
• Physical measurement and data analysis systems that use phenomena such as optics, electromagnetism, radiation, and gravity
• Applying scientific knowledge to identify and prototype emerging technologies
• Systems integration and data acquisition
• 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
• Data analysis, physics analysis, and applied statistics on a broad range of types of data including data from physical systems
• Capacity to dive deep on novel challenging problems in applying ML to mineral exploration, including understanding a complex domain of geology and mineral exploration practices as well as working with limited, disparate and noisy data sources
• Experience deploying sensors in the field
• Ability to take ownership and responsibility of large projects
• Intellectual curiosity and eagerness to learn about all aspects of mineral exploration, particularly in the geology domain. Open to working directly with geologists in the field. Enjoys constantly learning such that you are driving insights and innovations
• Ability to explain technical problems to and collaborate on solutions with domain experts who aren’t software developers. A strong communicator who enjoys working with colleagues across the company
• Excitement about joining a fast-growing early-stage company, comfort with a dynamic work environment, and eagerness to take on a range of responsibilities
• Keen not just to build cool technology, but to figure out what technical product to build to best achieve the business objectives of the company
• Ability to independently prioritize multiple tasks effectively

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 — 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
• 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

Preferred Qualifications

• Remote sensing
• Creating machine learning models on geospatial data
• Image processing or computer vision
• Project and team management

Benefits

• The US base salary range for this full-time exempt position is $200,000 - $230,000
• Location: Remote, Candidates can be located anywhere in the United States or Canada
• 10-20% travel required