

Data Scientist
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Scientist with a Data Engineering background, offering a 6-month contract in Central London at £600 per day. Key skills include Azure Analytics, Databricks, Power BI, and experience with data governance and AI frameworks.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
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💰 - Day rate
640
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🗓️ - Date discovered
September 25, 2025
🕒 - Project duration
More than 6 months
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🏝️ - Location type
Hybrid
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📄 - Contract type
Inside IR35
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🔒 - Security clearance
Unknown
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📍 - Location detailed
London Area, United Kingdom
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🧠 - Skills detailed
#Azure #Data Engineering #Data Governance #Data Pipeline #Data Lake #ML (Machine Learning) #Synapse #Databricks #Data Science #Data Ingestion #Data Automation #Microsoft Power BI #Scala #"ETL (Extract #Transform #Load)" #BI (Business Intelligence) #AI (Artificial Intelligence) #Data Management #Automation
Role description
Data Scientist (Hybrid Data Scientist & Data Engineer)
📍 Central London (Hybrid On-Site) | 💼 Financial Services
Contract Length: 6 months
Day Rate: £600 per day INSIDE of IR35
Overview:
My client, within Financial Services, are looking for a Data Scientist with a strong Data Engineering background to support the delivery of advanced data analytics solutions.
This role will involve building scalable data pipelines, applying AI frameworks, and leveraging Azure-based analytics tools to generate meaningful insights while ensuring robust governance and data management practices.
Key Responsibilities:
• Design and develop scalable data models and pipelines using Azure Analytics, Databricks, and Synapse.
• Apply AI frameworks across the Azure ecosystem to extract insights and drive business value.
• Develop and optimise Power BI dashboards and reporting solutions to provide actionable insights.
• Implement automation for data source collection, processing, and quality controls, ensuring data ingestion pipelines remain functional and reliable.
• Work within the clients data mesh framework, ensuring data is sourced from agreed and governed locations.
• Ensure best practices in data governance, avoiding uncontrolled data lake expansion.
• Collaborate with cross-functional teams to integrate and operationalise analytical models.
Essential Skills & Experience:
• Proven experience as a Data Scientist with a background in Data Engineering.
• Strong database development and management skills (IB/NCL, DBaaS).
• Hands-on expertise with Azure Analytics, Databricks, Synapse, and Power BI.
• Demonstrated experience in AI/ML frameworks applied within the Azure ecosystem.
• Strong understanding of data automation, ingestion, and governance.
• Experience working with or within a data mesh architecture.
Data Scientist (Hybrid Data Scientist & Data Engineer)
📍 Central London (Hybrid On-Site) | 💼 Financial Services
Contract Length: 6 months
Day Rate: £600 per day INSIDE of IR35
Overview:
My client, within Financial Services, are looking for a Data Scientist with a strong Data Engineering background to support the delivery of advanced data analytics solutions.
This role will involve building scalable data pipelines, applying AI frameworks, and leveraging Azure-based analytics tools to generate meaningful insights while ensuring robust governance and data management practices.
Key Responsibilities:
• Design and develop scalable data models and pipelines using Azure Analytics, Databricks, and Synapse.
• Apply AI frameworks across the Azure ecosystem to extract insights and drive business value.
• Develop and optimise Power BI dashboards and reporting solutions to provide actionable insights.
• Implement automation for data source collection, processing, and quality controls, ensuring data ingestion pipelines remain functional and reliable.
• Work within the clients data mesh framework, ensuring data is sourced from agreed and governed locations.
• Ensure best practices in data governance, avoiding uncontrolled data lake expansion.
• Collaborate with cross-functional teams to integrate and operationalise analytical models.
Essential Skills & Experience:
• Proven experience as a Data Scientist with a background in Data Engineering.
• Strong database development and management skills (IB/NCL, DBaaS).
• Hands-on expertise with Azure Analytics, Databricks, Synapse, and Power BI.
• Demonstrated experience in AI/ML frameworks applied within the Azure ecosystem.
• Strong understanding of data automation, ingestion, and governance.
• Experience working with or within a data mesh architecture.