Data Scientist, Principal

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.

• Identify and prioritize high-impact opportunities for data science across Hut 8s 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 organizations capabilities in statistical thinking machine learning experimentation and data-driven decision-making.

ABOUT YOU

• Bachelors or masters degree in Data Science Statistics Computer Science Engineering Mathematics Business Analytics or a related field; advanced degree preferred.
• 6 years of progressive experience in data science machine learning advanced analytics or a closely related discipline with a demonstrated record of leading high-impact initiatives.
• Strong proficiency in Python and SQL with advanced experience using statistical and machine learning libraries such as scikit-learn XGBoost PyTorch TensorFlow or comparable tools.
• Deep understanding of statistical modeling hypothesis testing experimental design model evaluation feature engineering and machine learning fundamentals.
• Experience developing and operationalizing models in production including model versioning reproducibility monitoring performance evaluation and collaboration with engineering teams.
• Demonstrated ability to work with time-series data forecasting optimization anomaly detection or other analytical methods relevant to complex operational and business problems.
• Experience applying large language models natural language processing retrieval-augmented generation intelligent agents or evaluation methods for AI-enabled products is strongly preferred.
• Strong ability to move from ambiguous business problems to rigorous analytical approaches practical recommendations and measurable outcomes.
• Familiarity with cloud data platforms such as Snowflake or BigQuery data warehouses data modeling data quality and lineage concepts.
• Excellent written and verbal communication skills including the ability to explain technical concepts model limitations uncertainty and tradeoffs to non-technical stakeholders and senior leaders.
• Demonstrated technical leadership mentoring ability and success working across business data software and infrastructure teams.
• Experience with Airflow or Luigi Git CI/CD cloud infrastructure Tableau Metabase semantic layers knowledge bases embeddings or metadata management is preferred.

ABOUT THE WORK ENVIRONMENT

This role is in office at our corporate headquarters in the Brickell area of Miami Florida. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.