Data Scientist (AI)

TL;DR

Data Scientist (AI/Geoscience): Building and applying predictive models and statistical methods to identify ore-forming processes and mineralization sites with an accent on geospatial analysis, Bayesian inference, and uncertainty quantification. Focus on developing proprietary data tools and physical-based models to accelerate critical metal discovery in a fast-paced environment.

Location: Remote-first, but must be legally authorized to work in United States, Canada, Australia, South Africa, United Kingdom, Zambia, Democratic Republic of the Congo, Namibia, Finland, Sweden, or Botswana.

Salary: $140,000–$240,000 (USD) plus equity and benefits.

Company

hirify.global is a mineral exploration company utilizing AI and proprietary technology to discover resources for the transition to a low-carbon economy.

What you will do

• Build models to make statistically valid predictions about compositional anomalies within the Earth’s crust.
• Develop and apply data processing, statistical, and physics-based techniques to geoscientific data.
• Curate geophysical, geochemical, and geological data for integration into proprietary systems.
• Create visualizations for evaluating model performance and data interaction.
• Collaborate with geoscientists to guide exploration targeting and field program design.
• Present solutions and project outcomes to external partners and stakeholders.

Requirements

• Minimum 4 years post-PhD or 8 years post-MS experience as a data scientist or data engineer.
• Must be legally authorized to work in US, Canada, Australia, South Africa, UK, Zambia, DRC, Namibia, Finland, Sweden, or Botswana.
• Strong proficiency in Python data science packages and software engineering practices.
• Expertise in applied statistics, Bayesian inference, and machine learning algorithms.
• Experience with collaborative software development using Git, CI/CD pipelines, and cloud computing.
• Willingness to travel internationally for exploration site visits.

Nice to have

• Experience creating machine learning models on geospatial data.
• Background in geostatistics.
• Expertise in image processing or computer vision.
• Experience with distributed computing for machine learning.

Culture & Benefits

• Early-stage startup environment with significant impact on global resource discovery.
• Remote-first workplace providing flexibility and autonomy.
• Work on complex scientific and physical system challenges alongside top-tier geoscientists.
• Competitive compensation packages including equity.
• Commitment to an inclusive and diverse workplace.