Data Scientist (Australia) Data Scientist (Australia) KoBold Metals Remote · Australia about 8 [...]

Seeds Renewables; Australia; Remote; AUD 120,000 - 180,000; Full time

Job summary

KoBold Metals is hiring a Data Scientist to accelerate mineral exploration using predictive models and science-based techniques. You will work with data scientists, software engineers, and geoscientists to build 2D/3D geologic predictions and design field programs to reduce uncertainty in discoveries.

The role emphasizes scalable data tools, visualizations, and collaboration with external partners, with a remote-first setup open to Australia-based candidates.

Qualifications

• Experience building predictive models using Python and statistical methods.
• Experience with collaborative software development (Git) and CI/CD pipelines.
• Familiarity with cloud computing resources and scalable data processing.
• Ability to build and evaluate models for geospatial data and exploration problems.
• Strong background in applied statistics, Bayesian inference, and ML algorithms.

Responsibilities

• Develop KoBold’s proprietary exploration tools and data models.
• curate geophysical, geochemical, geologic, and geographic data for the data system.
• Build predictive models for ore-grade mineralization in 2D/3D.
• Create visualizations to evaluate model performance and data features.
• Apply data processing and physics-based techniques to geoscientific data and guide exploration decisions.
• Collaborate with geoscientists and external partners to advance discovery.

Skills

Python

Git

CICD

Cloud computing

Predictive modeling

Geospatial analyses

Bayesian inference

Machine learning

Data processing

Tools

Git

AWS/GCP/Azure

Job description

The mining industry has steadily become worse at finding new ore deposits, requiring >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.

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.

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.

KoBold is privately held; investors include institutional asset managers T. Rowe Price 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.

We are hiring a Data Scientist 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

Work practices and motivation:

• Ability to design, scope and implement technical solutions to novel exploration problems
• 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.

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

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.

This position is full-time, exempt.

Location: Location: KoBold is a remote first workplace, we are open to candidates currently residing anywhere in Australia, with a preference for Western Australia.

About the company: The mining industry has steadily become worse at finding new ore deposits, requiring >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 ...

/board/blackinenviron/job/67476031/data-scientist-australia?source=blackinenviron_board&queryID=8d1799b675a70ac29247711fea12bbb4