Senior Software Engineer, Decision Science

At least 5 years of experience in decision science with a strong software engineering focus (closer to 10 is ideal). Track record of building production quality data processing solutions or tooling that have delivered business value. Proficiency with foundational ML concepts, including statistical, traditional, and deep-learning approaches. Proficiency in Python, ideally including array-based packages such as xarray and numpy. Deep experience with measured scientific data. Experience in visualizing scientific data for domain experts. Experience in MLOps and building robust ML systems. Drive to increase the velocity and effectiveness of data scientists in workflows. Capacity to dive deep on novel challenging problems in applying decision science to mineral exploration. Collaborative attitude to work with stakeholders from diverse backgrounds.

Architect, implement, and maintain decision science libraries for mineral exploration analyses. Build tooling to increase decision-making velocity, including rapid prototyping, experimentation, evaluation, and simulation frameworks. Turn R&D into robust, scalable pipelines and organize ML models for repeatability. Apply and coach team members on engineering best practices, writing robust, testable, and composable code. Collaborate with data scientists, geoscientists, and engineers to invent decision science technology for mineral exploration. Occasionally travel to exploration sites globally for observation and technology design.