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Hut 8 operates large-scale data centers for next-generation computing workloads including AI, colocation, cloud, and Bitcoin mining. This Principal Data Scientist role is a technical leadership position focused on enterprise data strategy, governance, and analytics.
Key Responsibilities:
- Own or contribute to the enterprise data inventory, including priority systems, data owners, business definitions, lineage, dependencies, and quality gaps.
- Translate business processes and stakeholder needs into data requirements, source mappings, data models, quality rules, and measurable acceptance criteria.
- Partner with Data Operations and Software Engineering to improve ingestion, transformation, integration, monitoring, governance, and lifecycle management.
- Prepare and maintain enterprise data for agentic workflows by supporting semantic layers, knowledge bases, metadata, retrieval indexes, data contracts, access controls, and evaluation datasets.
- Apply data science and analytical methods to develop reusable models, reports, dashboards, and decision-support products.
- Monitor the reliability and usefulness of data products and agentic workflows, using quality findings and user feedback to drive continuous improvement.
- Communicate data limitations, recommendations, and business impact clearly to technical and non-technical stakeholders.
The role is in-office at Hut 8's corporate headquarters in the Brickell area of Miami, Florida.
Requirements:
- Bachelor's or master's degree in data science, Statistics, Computer Science, Engineering, Business Analytics, Mathematics, or a related field.
- 6+ years of experience in data science, enterprise data management, analytics engineering, data engineering, or a closely related discipline.
- Strong proficiency in Python and SQL, with experience working with relational databases, data warehouses, and ETL/ELT processes.
- Familiarity with cloud data platforms such as Snowflake or BigQuery, data modeling, data quality, and lineage concepts.
- Understanding of machine learning and AI concepts, including large language models, natural language processing, retrieval-augmented generation, and intelligent agents.
- Strong ability to connect business processes to data structures, analytical outputs, and practical implementation plans.
- Clear written and verbal communication skills and the ability to work effectively across technical and business teams.
- Preferred: experience with semantic layers, ontologies, metadata management, knowledge bases, embeddings, agent evaluation, Airflow or Luigi, Tableau, Metabase, Git, CI/CD, or cloud infrastructure.
