资深数据科学家
Staff Data Scientist
数据科学家(高级职员、职员及高级职位可选)
关于公司
KoBold Metals 是一家利用人工智能探索我们向低碳经济转型所需金属的矿产勘探公司。KoBold 的业务是发现、定义、扩展和开发矿产资源,KoBold 的目标是实现勘探成功率的突破性提升:我们旨在更快地发现更多一级资源,并减少失败率。
KoBold 拥有超过 80 个勘探项目组合,涵盖镍、铜、钴和锂,这些项目从全资到与大型企业、初级勘探公司和勘探者合作均有涉及。
我们的团队汇聚了勘探地质学、数据科学、软件工程、运营和商业领域的顶尖人才。在加入 KoBold 之前,KoBold 团队成员几乎发现了近 20 处矿藏。我们的勘探项目由地质学家和数据科学家共同领导,他们制定勘探假设,严格量化对地下结构理解中的不确定性,并设计最有效地减少不确定性的数据采集方案,这些方案依托于数据科学家和软件工程师开发的一整套专有勘探技术。我们的实地项目验证并改进了该系统,已显示出相较于传统勘探方法的显著提升。
KoBold 为私人持有,我们的投资者包括:机构资产管理公司 T. Rowe Price 和加拿大养老基金投资公司;科技风险投资公司 Andreessen Horowitz、比尔·盖茨的 Breakthrough Energy Ventures、BOND Capital、Standard Investments 和 Sam Altman 的 Apollo Projects;以及领先的自然资源公司 Equinor、三菱和 BHP。
我们正在招聘数据科学家以帮助加速我们的使命。
职位简介
在此职位中,您将构建预测模型,并应用广泛的科学计算、统计和基于物理的方法,寻找存在成矿过程证据的地方,并预测 2D 和 3D 中矿化品位的位置。您将帮助建立支撑我们勘探计划的全球数据集,仔细关注识别和量化数据及预测中的不确定性。您将创建模型并开发软件以加速关键电池金属的发现。
您将加入一个出色的数据科学家和工程师团队,并将与他们协作工作
查看英文原文
Data Scientist (Senior Staff, Staff, & Senior roles available)
About the company
KoBold Metals is a mineral exploration company using AI to explore for the metals we need for our transition to a low-carbon economy. KoBold’s business is discovering, defining, expanding, and developing mineral resources, and KoBold’s objective is to achieve a step-change improvement in exploration success: we aim to discover more tier 1 resources, faster, and with fewer failures.
KoBold has a global portfolio of more than 80 exploration properties targeting nickel, copper, cobalt, and lithium, which range from 100%-owned to partnerships with both majors, junior explorers, and prospectors.
Our team includes the best of the industry in exploration geoscience, data science, software engineering, operations, and business personnel. Prior to joining KoBold, KoBold team members have made nearly 20 discoveries. Our exploration programs are co-led by our geoscientists and data scientists, who develop exploration hypotheses, rigorously quantify uncertainty in our understanding of the subsurface, and design data collection programs that most effectively reduce uncertainty, drawing upon a large suite of proprietary exploration technology built by our data scientists and software engineers. Our field programs validate and improve the system and have demonstrated material improvements over conventional exploration methods
KoBold is privately held and our investors include: institutional asset managers T. Rowe Rice and Canada Pension Plan Investments; technology venture capitalists Andreessen Horowitz, Bill Gates’s Breakthrough Energy Ventures, BOND Capital, Standard Investments, and Sam Altman’s Apollo Projects; and leading natural resources companies Equinor, Mitsubishi, and BHP.
We are hiring a Data Scientists to help accelerate our mission.
About the position
In this role, you will build predictive models and apply a wide range of scientific computing, statistical, and physics-based methods to find places where there is evidence of ore-forming processes at work and to predict the locations of ore-grade mineralization in 2D and 3D. You will help build a worldwide dataset that underlies our exploration program, with careful attention to identifying and quantifying uncertainty in the data and in our predictions. You will create models and develop software to accelerate discovery of critical battery metals.
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 create 2D and 3D geologic 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.
Ultimately, your role is to help KoBold make valuable discoveries by building data tools to solve scientific problems. As one of the early members of this team, you will help build these tools from the ground up.
Responsibilities
The Data Scientist will:
- Help develop KoBold’s proprietary software exploration tools.
- Find and curate 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 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.
Qualifications
A great Data Scientist candidate will have:
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.
- Cloud computing resources.
- Building predictive models, applying them to different problems, and evaluating and interpreting the results.
- Data from a variety of physical systems.
- Geospatial analyses and visualizations.
Technical knowledge:
- Broad skills in and knowledge of applied statistics and Bayesian inference
- Substantial understanding of machine learning algorithms
Training and work experience:
- An advanced degree in the physical sciences, engineering, computer science, or mathematics.
- A minimum work experience of 4 years post PhD or 8 years post MS, ideally as a data scientist or data engineer.
- Experience leading technical teams to apply novel scientific approaches to core business problems
Work practices and motivation:
- Ability to take ownership and responsibility of large projects.
- Ability to explain technical problems to and collaborate on solutions with domain experts.
- Communicates well on a collaborative, cross-functional team.
- 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.
- Intellectual curiosity and eagerness to learn about all aspects of mineral exploration, particularly in the geology domain.
- Enjoys constantly learning such that you are driving insights through using our tools in exploration and willing to work directly with geologists in the field.
- 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.
- A valid passport and willingness to travel to observe our work at Mingomba or at an exploration site around the world.
It is also helpful but not required to have experience with:
- Creating machine learning models on geospatial data
- Geostatistics
- Image processing or computer vision
- Distributed computing applications for machine learning and other computations
What to Expect
Joining KoBold means getting the opportunity for hands-on exposure to our exploration projects around the world. All employees are expected to travel to project sites, with a minimum of one week per year. Field-facing and technical roles spend significantly more time in the field.
KoBold Metals is an equal opportunity workplace and an affirmative action employer. We are committed to equal employment opportunity for people of any race, color, ancestry, religion, sex, gender identity, sexual orientation, marital status, national origin, age, citizenship, disability, or veteran status.
The US base salary range for this full-time exempt position is $140,000 - $260,000 plus equity and benefits, including 401k match.
Location: KoBold is a remote-first workplace. All candidates must be legally authorized to work in one of the following countries: United States, Canada, Australia, South Africa, United Kingdom, Zambia, Democratic Republic of the Congo, Namibia, Finland, Sweden, or Botswana.
Originally posted on Himalayas