Data Scientist, Principal at Hut 8

<div class="content-intro"><p>&nbsp;</p> <p>&nbsp;</p></div><p><strong>ABOUT THE ROLE</strong></p> <p>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.<br><br>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.</p> <div>Some of the key responsibilities you should expect are the following:</div> <ul> <li>Identify and prioritize high-impact opportunities for data science across Hut 8’s technology, energy, infrastructure, AI, colocation, cloud, and mining businesses.</li> <li>Translate business questions into clear analytical frameworks, hypotheses, modeling strategies, success metrics, and measurable acceptance criteria.</li> <li>Develop, validate, and deploy predictive, forecasting, optimization, classification, ranking, and anomaly-detection models that solve complex business problems.</li> <li>Apply statistical analysis, experimental design, hypothesis testing, causal inference, and scenario modeling to evaluate decisions and quantify business impact.</li> <li>Lead the end-to-end data science lifecycle, including exploratory analysis, feature engineering, model development, validation, deployment, monitoring, and iteration.</li> <li>Build reusable analytical products, decision-support tools, models, reports, and visualizations that enable leaders and operating teams to act with greater speed and confidence.</li> <li>Establish standards for model evaluation, interpretability, reproducibility, documentation, experimentation, and responsible use of machine learning.</li> <li>Develop evaluation frameworks for AI and agentic workflows, including benchmark datasets, retrieval and response quality measures, groundedness, relevance, and user feedback analysis.</li> <li>Partner with Data Operations and Software Engineering on source data requirements, data quality issues, feature pipelines, production integrations, model serving, and monitoring.</li> <li>Use data quality findings, model performance, and stakeholder feedback to improve analytical products and ensure they remain reliable and useful over time.</li> <li>Communicate technical findings, uncertainty, recommendations, and business impact clearly through concise narratives, visualizations, reports, and executive presentations.</li> <li>Mentor data scientists and raise the organization’s capabilities in statistical thinking, machine learning, experimentation, and data-driven decision-making.</li> </ul> <p><strong>ABOUT YOU</strong></p> <ul> <li>Bachelor’s or master’s degree in Data Science, Statistics, Computer Science, Engineering, Mathematics, Business Analytics, or a related field; advanced degree preferred.</li> <li>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.</li> <li>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.</li> <li>Deep understanding of statistical modeling, hypothesis testing, experimental design, model evaluation, feature engineering, and machine learning fundamentals.</li> <li>Experience developing and operationalizing models in production, including model versioning, reproducibility, monitoring, performance evaluation, and collaboration with engineering teams.</li> <li>Demonstrated ability to work with time-series data, forecasting, optimization, anomaly detection, or other analytical methods relevant to complex operational and business problems.</li> <li>Experience applying large language models, natural language processing, retrieval-augmented generation, intelligent agents, or evaluation methods for AI-enabled products is strongly preferred.</li> <li>Strong ability to move from ambiguous business problems to rigorous analytical approaches, practical recommendations, and measurable outcomes.</li> <li>Familiarity with cloud data platforms such as Snowflake or BigQuery, data warehouses, data modeling, data quality, and lineage concepts.</li> <li>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.</li> <li>Demonstrated technical leadership, mentoring ability, and success working across business, data, software, and infrastructure teams.</li> <li>Experience with Airflow or Luigi, Git, CI/CD, cloud infrastructure, Tableau, Metabase, semantic layers, knowledge bases, embeddings, or metadata management is preferred.</li> </ul> <p><strong>ABOUT THE WORK ENVIRONMENT</strong></p> <p><span class="NormalTextRun SCXW126023513 BCX0">This role is </span><span class="NormalTextRun SCXW126023513 BCX0">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.</span></p>