Data Scientist

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Data SciencemidGreat Work, England, UKremotecontractData Infrastructure and Analytics and Data Security Software ProductsMicrosoft FabricPower BISQLPythonFabric Data AgentsOneLakeLakehousesData Warehousesposted 20 Jul
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Data Scientist – Contract Position – HIRING ASAP Location: Remote (EU or UK) Start Date: ASAP Duration: 12 months Daily Rate: €300 per day (OUTSIDE IR35 if UK Based) Requirements: * 4+ years in data science, analytics engineering, or a closely related field, with demonstrated delivery of production-grade data and ML solutions. * Hands-on experience with Microsoft Fabric, including OneLake, Lakehouses, Data Warehouses, and Power BI semantic models. * Practical experience with Fabric IQ, specifically building or maintaining ontologies that define business entities, relationships, properties, rules, and actions, and aligning them with existing Power BI semantic models. (Note: ontology is currently in preview, so candidates from late-2025/2026 hands-on programs are realistic.) * Experience designing, building, and publishing Fabric Data Agents, including the low-code experience and the Fabric Data Agent Python SDK; understanding that Data Agents operate under the end user's identity and respect underlying Fabric data permissions (Entra ID). * Strong SQL and Python; familiarity with semantic modeling concepts (measures, hierarchies, dimensions). * Understanding of data governance, lineage, and permissions-aware access in an enterprise context. Preferred / nice-to-have: * Experience with Fabric Real-Time Intelligence (Eventhouse, live signals) and graph in Fabric for cross-domain reasoning. * Familiarity with Operations Agents and human-in-the-loop approval patterns (e.g., Teams-based action approval, autonomous-rule promotion). * Exposure to the broader Microsoft IQ context layer (Work IQ, Foundry IQ) and to exposing ontologies to external agents via MCP. * Experience with NL2Ontology / natural-language querying over a semantic layer. * Background treating the semantic layer as production infrastructure — versioning, testing, and governing ontologies with the same discipline as data pipelines.