SC Cleared Senior Data Analyst
Location: Remote working and onsite in Newcastle once a month
Duration: 6 months
Security Clearance: Must hold Active SC
Rate: £500 -£650 Inside IR35
Role Specification:
- Adoption of Analysis Techniques: Help the organisation adopt a wide range of analysis and synthesis techniques, continually assuring, improving, and innovating practices to generate clear and valuable findings.
- Stakeholder Communication: Mediate between people, mend relationships, and communicate with stakeholders at all levels.
- Expectation Management: Manage stakeholder expectations and moderate discussions about high risk and complexity, even within constrained timescales.
- Representation: Speak on behalf of and represent the community to large audiences inside and outside of government.
- Influence and Strategy: Influence senior stakeholders in data approaches and set the strategy to enable your teams to produce effective and influential visualisations.
- Standard Adherence: Ensure adherence to organisation-wide standards and guidelines, and suggest appropriate ways to improve them.
- Team Development: Ensure your team has the training, skills, and support required to produce high-quality data visualisations that are insightful and actionable.
- Continuous Improvement: Implement feedback gathering to support continuous improvement.
- IT and Mathematical Skills: Demonstrate knowledge and experience of applying IT and mathematical skills, and act as a recognised specialist and adviser in these areas.
- Project Management: Demonstrate knowledge and experience of applying project management methodologies, overseeing projects within a data analytics team.
- Data Governance: Ensure data management and governance processes are in place and adhered to for the products and services your teams provide. Define strategies for continual improvement of data management practices and compliance with data governance policies.
- Data Modelling: Understand different ways to model data to maximise its use and value. Ensure data is modelled appropriately and that modelling standards exist and are complied with.
- Data Integration: Understand various data integration tools and patterns, ensuring your teams have the support and training needed to use the most appropriate methods.
- Collaboration: Build relationships with other senior data professionals (e.g., data architecture, data engineering, data science) to share best practices and continually improve data modelling and integration processes and standards.
- Verification and Validation: Show a deep understanding of relevant data sources, tools, and systems, using appropriate approaches for verifying and validating data and analysis.