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KoBold Metals

Data Scientist, Hyperspectral Remote Sensing

Hybrid, RemoteFull time roleEarly Career

About 1 year ago

About the Job

<h3>Data Scientist, Hyperspectral Remote Sensing</h3><p>The mining industry has steadily become worse at finding new ore deposits, requiring &gt;10X more capital to make discoveries compared to 30 years ago. The easy-to-find, near-surface deposits have largely been found, and the industry has chronically under-invested in new exploration technology, relying on the manual techniques of yesteryear – even as demand accelerates for copper, lithium, and other metals to build electric vehicles, renewable energy, and data centers.</p><p>KoBold builds AI models for mineral exploration and deploys those models—alongside our novel sensors—to guide decisions on KoBold-owned-and-operated exploration programs. In the six years since founding, KoBold has become by far both the largest independent mineral exploration company and the largest exploration technology developer. Our data scientists and software engineers, who come from leading technology companies, jointly lead exploration programs with our renowned exploration geologists.</p><p>KoBold has proven its first discovery with materially less capital than the industry average and found one of the best copper deposits ever discovered: the copper is far more concentrated than the global average of copper mines, and this asset alone is expected to generate meaningful revenue for decades. KoBold has a portfolio of more than 60 other projects, each of which has the potential for another high-quality discovery.</p><p>KoBold is privately held; investors include institutional asset managers T. Rowe Rice and Canada Pension Plan Investments; technology venture capitalists Andreessen Horowitz, Breakthrough Energy Ventures, BOND Capital, and Standard Investments; and natural resources companies Equinor, BHP, and Mitsubishi.</p><p><span style="font-weight:400;">We are hiring a Data Scientist to help accelerate our mission.</span></p><p><strong>About the position</strong></p><p>In this role, you will build predictive models and apply a wide range of scientific computing, statistical, and physics-based methods to transform remote sensing data, including multi- and hyper-spectral, into actionable insights that guide our exploration programs. You will further develop KoBold’s in-house remote sensing instrumentation and develop modeling tools to optimize further data collection efforts. You will be creating insights that accelerate discovery of critical battery metals.</p><p>You will join an outstanding team of data scientists and engineers and will work closely with KoBold’s world-renowned geoscientists to incorporate our best understanding of the chemical and physical processes that create ore deposits. Working with your geoscience colleagues, you will identify new opportunities and technologies for geophysical data collection, create predictions, identify exploration targets, design field programs to collect data, and use that data to reduce the uncertainty in our predictions and guide the next phase of field work.</p><p>Ultimately, your role is to help KoBold make valuable discoveries by building and deploying next generation hardware and analysis techniques to solve scientific problems. </p><strong>Responsibilities</strong><p>The Hyperspectral Data Scientist will:</p><ul><li>Apply state-of-the-art analysis techniques to multi- and hyper-spectral remote sensing data</li><li>Model and simulate remote sensing instruments to improve data collection and guide development of future instruments</li><li>Help develop KoBold’s proprietary software exploration tools.</li><li>Find and curate open source remote sensing data and integrate it into KoBold’s proprietary data system.</li><li>Build models to make statistically valid predictions about the locations of compositional anomalies within the Earth’s crust.</li><li>Create effective visualizations for evaluating model performance and enabling rapid interaction with the underlying data and key features.</li><li>Develop and apply a range of data processing, statistical, and physics-based techniques to geoscientific data, including both reflectance and emissivity spectroscopy, and use the results to guide our targeting efforts and inform our acquisition and exploration decisions.</li><li>Present to and collaborate with our external partners and stakeholders.</li></ul><strong>Qualifications</strong><p>A great Hyperspectral Scientist candidate will have:</p><ul><li>A successful track record of working with remote sensing instrumentation, especially reflectance and emissivity spectroscopy, and developing and deploying state-of-the-art spectral analysis techniques.</li></ul><p>Technical skills, including extensive experience with:</p><ul><li>Physical measurement and data analysis systems. </li><li>Applying scientific knowledge to identify and prototype emerging technologies</li><li>Systems integration and data acquisition.</li><li>Python’s data science packages and general software engineering practices.</li><li>Collaborative software development (git), and familiarity with software engineering best practices like unit test / integration test suites, and CICD pipelines.</li><li>Using cloud computing resources to perform scientific analysis at scale</li><li>Building a wide variety of predictive models, applying them to different problems, and evaluating and interpreting the results.</li><li>Working with a broad range of types of data including data from physical systems.</li><li>Geospatial analyses and visualizations.</li></ul><p>Technical knowledge:</p><ul><li>Atmospheric corrections for remote sensing data</li><li>Broad skills in and knowledge of data analysis, physics, and applied statistics.</li></ul><p>Training and work experience:</p><ul><li>An advanced degree in the physical sciences, engineering, computer science, or mathematics.</li><li>Post-degree work experience as a scientist or engineer.</li></ul><p>Work practices and motivation:</p><ul><li>Ability to take ownership and responsibility of large projects.</li><li>Enjoys constantly learning such that you are driving insights and innovations.</li><li>Ability to explain technical problems to and collaborate on solutions with domain experts who aren’t software developers.</li><li>Excitement about joining a fast-growing early-stage company, comfort with a dynamic work environment, and eagerness to take on a range of responsibilities.</li><li>Ability to independently prioritize multiple tasks effectively.</li></ul><p>It is also helpful but not required to have experience with:</p><ul><li>Image processing or computer vision</li><li>Geophysical data, instrumentation, and inverse problems</li><li>Project and team management</li></ul><p>KoBold Metals is an equal opportunity workplace and an affirmative action employer. We are committed to equal employment opportunities for people of any race, color, ancestry, religion, sex, gender identity, sexual orientation, marital status, national origin, age, citizenship, marital status, disability, or veteran status.</p><p>The US base salary range for this full-time exempt position is $140,000-$220,000.</p><p>Location: KoBold is a remote first workplace, we are open to candidates currently residing anywhere in the United States or Canada. All candidates must be authorized to legally work in either the United States or Canada</p>

About the Company

KoBold Metals Logo

KoBold Metals

Berkeley, CA, USA

51-100

<p>KoBold Metals<em><sup>&reg;</sup></em>&nbsp;is a rapidly growing Silicon Valley start-up using AI to enable the transition to electrification and help solve climate change. We are backed by Bill Gates&rsquo; Breakthrough Energy Ventures, a16z, Bond Capital, Sam Altman, T Rowe Price, and other premier VCs.</p> <p>Our team includes the best of the industry in exploration geoscience, data science, software engineering, and business personnel. KoBold&rsquo;s world-renowned geoscientists have made nearly 20 discoveries. They work on joint teams with outstanding data scientists, who have PhDs in physics, math, materials science, and geophysics. And our technology backbone has been built from scratch by our team of software engineers who are alumni of top Silicon Valley tech companies.</p>

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