Hut 8 brings exceptional people together to solve the world’s most consequential problems at the intersection of energy and technology. Today, that means building infrastructure for AI at a pace and scale without precedent. Tomorrow, it could mean powering a new era of innovation through robotics, advanced manufacturing, or an industry that does not yet exist. Whatever the technology demands, our ambition holds: to build the defining physical infrastructure company of our generation.

We look for thinkers and builders with the rigor, humility, and ownership to solve problems at this scale. They start from zero and choose truth over tradition. They back the best idea, whatever its source. They bet on themselves and embrace the hard truths that force them to grow. Our commitment is to keep the path from idea to execution short, trust them with critical decisions and the work that follows, and surround them with colleagues whose curiosity extends beyond their expertise.

ABOUT THE ROLE

As Principal, Data Scientist, you will lead the development of advanced analytical and machine learning solutions that help Hut 8 make better decisions, improve performance, and create new products and capabilities. You will work across the organization to frame ambiguous business problems, identify high-value opportunities for data science, and turn complex data into models, insights, and decision-support products with measurable impact.

This is a hands-on technical leadership role. You will shape the data science roadmap, establish strong modeling and experimentation practices, and serve as a senior advisor to business and technical leaders. You will partner with Data Operations and Software Engineering to ensure reliable access to well-defined data, while maintaining primary ownership of the analytical approach, model quality, and business outcomes.

Some of the key responsibilities you should expect are the following:

Identify and prioritize high-impact opportunities for data science across Hut 8’s technology, energy, infrastructure, AI, colocation, cloud, and mining businesses.
Translate business questions into clear analytical frameworks, hypotheses, modeling strategies, success metrics, and measurable acceptance criteria.
Develop, validate, and deploy predictive, forecasting, optimization, classification, ranking, and anomaly-detection models that solve complex business problems.
Apply statistical analysis, experimental design, hypothesis testing, causal inference, and scenario modeling to evaluate decisions and quantify business impact.
Lead the end-to-end data science lifecycle, including exploratory analysis, feature engineering, model development, validation, deployment, monitoring, and iteration.
Build reusable analytical products, decision-support tools, models, reports, and visualizations that enable leaders and operating teams to act with greater speed and confidence.
Establish standards for model evaluation, interpretability, reproducibility, documentation, experimentation, and responsible use of machine learning.
Develop evaluation frameworks for AI and agentic workflows, including benchmark datasets, retrieval and response quality measures, groundedness, relevance, and user feedback analysis.
Partner with Data Operations and Software Engineering on source data requirements, data quality issues, feature pipelines, production integrations, model serving, and monitoring.
Use data quality findings, model performance, and stakeholder feedback to improve analytical products and ensure they remain reliable and useful over time.
Communicate technical findings, uncertainty, recommendations, and business impact clearly through concise narratives, visualizations, reports, and executive presentations.
Mentor data scientists and raise the organization’s capabilities in statistical thinking, machine learning, experimentation, and data-driven decision-making.

ABOUT YOU

Bachelor’s or master’s degree in Data Science, Statistics, Computer Science, Engineering, Mathematics, Business Analytics, or a related field; advanced degree preferred.