Data Scientist (Python, GCP, Microsoft technologies) - Inside IR35 - Fully Remote Working
Europa Search
2 days ago
Role details
Contract type
Temporary contract Employment type
Full-time (> 32 hours) Working hours
Regular working hours Languages
English Experience level
SeniorJob location
Remote
Tech stack
Artificial Intelligence
Data analysis
Azure
Google BigQuery
Cloud Storage
Python
Machine Learning
Microsoft Software
Microsoft SQL Server
Power BI
Data Processing
Google Cloud Platform
Job description
We are seeking an experienced Data Scientist to join a high-performing data team within the energy sector. This role has been created due to existing subcontractors completing or exiting their current engagements, and budget approval is already in place.
The successful candidate will work closely with the Head of Data and wider stakeholders to deliver data-driven insights and scalable solutions across the business., * Design, build, and deploy data science solutions to support business and operational objectives
- Work with large and complex datasets to develop predictive models, analytics, and insights
- Develop and maintain data pipelines and models using Python
- Leverage Google Cloud Platform (GCP) services for data processing, modelling, and deployment
- Integrate solutions with Microsoft technologies where required
- Collaborate with cross-functional teams including engineering, analytics, and business stakeholders
- Communicate findings and recommendations clearly to both technical and non-technical audiences
Requirements
- 5+ years' experience working as a Data Scientist
- Strong proficiency in Python for data analysis and modelling
- Hands-on experience with GCP (eg BigQuery, Cloud Storage, Vertex AI or similar)
- Experience working with Microsoft technologies (eg Azure services, SQL Server, Power BI, or related tools)
- Strong understanding of data modelling, statistics, and machine learning techniques
- Ability to work independently in a contract environment
Desirable Experience
- Previous experience within the energy industry
- Experience working in large or enterprise-scale data environments