As Data Analyst, you will:
• A data analyst collects, organises and studies data to provide business insight.
• Apply tools and techniques for data analysis and data visualisation (including the use of business information tools)
• Identify, collect and migrate data to and from a range of systems.
• Manage, clean, abstract and aggregate data alongside a range of analytical studies on that data.
• Manipulate and link different data sets.
• Summarise and present data and conclusions in the most appropriate format for users.
• Analytical and problem-solving skills. You can apply analytical techniques to present a solution.
• Communication skills. You have strong verbal and written communication skills and understand how to share insights with stakeholders.
• Data management. You understand data sources, data organisation and storage.
• Data modelling, data cleansing, and data enrichment skills. You understand conceptual, logical and physical data manipulation and modelling and can develop knowledge of data cleansing and standardisation.
• Data visualisation. You can interpret requirements and present data in a clear and compelling way, using graphical representations and data visualisations.
• Logical and creative thinking skills. You can approach a problem, applying logic and creativity.
• Project management skills. You know how to work with stakeholders to gather requirements and deliver findings. (Senior/Lead Data Analysts may oversee projects within a data analytics team.)
• Proven IT and mathematical skills. You have proven IT and mathematical skills, demonstrated through relevant qualifications or work experience.
• Quality assurance, validation and data linkage abilities. You know how to conduct data quality assurance, validation and linkage.
• Statistical methods and data analysis skills. You know about statistical methodologies and data analysis techniques.
• Experience of building and drawing inference from logistic and linear regression analysis and hypothesis testing, knowing when to deploy different techniques and their meaning in different contexts
• Equivalent experience of at least one of discrete event simulation or predictive analytics.
• Experience with R/Python.
• At least 12 months of experience working with large surveys or datasets, ideally in government or related industries (including academia).
It would be great to also have:
• Experience building dashboards, preferably in Power BI and R Shiny.
• Experience with data dashboard design and standards.
• Experience using sensitive datasets, adapting customer requirements to appropriate access privileges.
• Experience with R/Python/SQL.
• Comfortable operating at pace to changing requirements and tailoring work accordingly.