Staff ML Data Scientist

About the Role / Overview

The role involves technical execution and team leadership in the field of data science and geospatial data processing.

Responsibilities / What You'll Do

• Architect, implement, and maintain foundational data science models for distributed processing of large-scale geospatial data with direct application to Kobold's mineral exploration projects and deep collaboration with geoscientists.
• In collaboration with our engineering team, build tooling to increase the velocity and rigor of our machine learning capabilities to derive insights from remote sensing data
• Improve upon current processing pipelines for lidar, high resolution imagery, and hyperspectral data
• 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

Team Leadership

• Lead and grow the team of 3-6 field engineers and data scientists collecting and processing terabytes of hyperspectral and lidar data around the globe.
• Run our global airborne data collection program - working closely with internal mineral exploration teams, legal, contracting, and operations as well as external aviation partners to safely and successfully deploy our custom sensors, backhaul and rapidly process data.
• Lead the week-to-week working cadence and quarterly planning process - setting clear goals, timelines, and technical objectives - weighing company priorities and executing a roadmap to improve our capabilities to collect data and derive mineral exploration insights.

This role creates positive change by developing AI models and algorithms for mineral exploration that enable the discovery of copper, lithium, and other metals needed for electric vehicles, renewable energy, and data centers, supporting the energy transition with more efficient and less capital-intensive methods than traditional mining approaches.

• At least 5 years of experience as a software engineer, data scientist or ML engineer, though most great candidates will have closer to 10. Recent bachelor's/master's/PhD candidates are unlikely to be competitive.
• 2+ years managing technical teams in complex, multidisciplinary projects
• Track record of building production quality data processing solutions or tooling that have delivered business value
• Proficiency with foundational concepts of ML, including statistical, traditional and deep-learning approaches
• Proficiency in Python, ideally including array-based packages such as xarray and numpy
• Proficiency in scaling complex data operations across distributed computing resources, using tools such as Spark or Dask
• 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
• Collaborative attitude to work with stakeholders with different backgrounds (data scientists, geoscientists, software engineers, operations)
• Experience with multispectral remote-sensing data from a variety of sources

The US base salary range for this full-time exempt position is $175,000 - $250,000. KoBold Metals is an equal opportunity workplace and an affirmative action employer 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.

KoBold builds AI models for mineral exploration and deploys those models—alongside novel sensors—to guide decisions on KoBold-owned-and-operated exploration programs, aiming to discover copper, lithium, and other metals needed for electric vehicles, renewable energy, and data centers with less capital than industry averages.