Data Scientist/Graph Data Engineer - Data Scientist/Graph Data Engineer £400 per day

• Design, develop and maintain Python-based data solutions.
• Model and analyse complex relationships using graph-based approaches.
• Build and optimise graph database solutions, particularly using Neo4j.
• Develop entity resolution and record linkage capabilities across disparate datasets.
• Design scalable data models that accurately represent real-world entities and relationships.
• Implement robust testing, validation and quality assurance processes.
• Contribute to CI/CD pipelines and automated deployment practices.
• Ensure adherence to data governance, security, compliance and risk management standards.
• Produce high-quality technical documentation and knowledge-sharing materials., The ideal candidate will bring a combination of Python development, graph database expertise, entity resolution and data modelling experience. Candidates whose experience is primarily focused on traditional machine learning or standard ETL/data pipeline engineering may be less aligned to the requirements of this role.

We are seeking an experienced Data Scientist/Data Engineer with strong expertise in graph data, entity resolution and Python development to join a high-profile public sector programme., * Strong commercial experience developing solutions in Python.

• Experience working with graph databases, ideally Neo4j.
• Proven expertise in entity matching, entity resolution, record linkage or identity resolution.
• Strong understanding of data modelling and relationship-driven data structures.
• Experience working with large and complex datasets.
• Knowledge of software engineering best practices including testing, validation and documentation.
• Experience implementing or working within CI/CD environments.
• Good understanding of data governance, data quality, security and risk management.
• Active SC Clearance is required.

Desirable Skills

• Experience with Splink or similar probabilistic record linkage tools.
• Experience delivering solutions within highly regulated or large-scale public sector environments.
• Familiarity with graph analytics and network-based data analysis techniques.