Data Analyst

• Data analysis and reporting: Conducting in-depth data analysis, generating reports, and providing actionable insights for client projects
• Data and BI visualisation: Producing BI dashboards using industry-standard tools - Power BI, Tableau, Quicksight etc
• Client interaction: Collaborating with clients to understand their needs, translating these into analytical solutions, and presenting findings in a clear, actionable manner

• Analysis and synthesis
• Application of analytical techniques: Proficiency in applying various analytical methods such as statistical analysis, data mining, and qualitative analysis. Ability to select and apply appropriate techniques based on the context and research data
• Synthesis of research data: Experience in synthesising research data to present actionable insights and solutions. Ability to articulate the impact of their analysis on decision-making and problem-solving
• Engagement with sceptical colleagues: Effective communication skills to engage and gain buy-in from sceptical colleagues
• Data Management
• Good understanding of data sources and storage: Familiarity with common data sources and general knowledge of data organisation and storage practices. Willingness to maintain data accuracy and accessibility
• Awareness of data governance: Understanding of data governance standards and a commitment to following data quality practices set by the team
• Continuous improvement: Ability to contribute to improvements in data management practices by supporting documentation, learning from team training, and actively participating in discussions
• Toolset support: Experience with using data management tools, with a willingness to learn more about maintaining efficiency and integration
• Compliance with data governance policies: Basic understanding of data governance policies, with a focus on following data security and ethical standards
• Data cleansing and standardisation: Experience in resolving data quality issues and ensuring data accuracy through cleansing and standardisation techniques
• Exposure to data integration tools: Basic experience with ETL tools for data integration and storage, with a focus on learning how to ensure data interoperability with other datasets
• Collaboration with data professionals: Some experience working with other data professionals, with a focus on learning and improving data modelling and integration practices through teamwork
• Understanding visualisation requirements: Ability to understand data visualisation needs and create simple, visually appealing representations suited to the audience
• Good working knowledge of visualisation tools: Experience using tools like Tableau, Power BI, or Python libraries (e.g., Matplotlib, Seaborn), with a willingness to learn how to choose the right visualisation type for different data sets
• Awareness of visualisation standards: Understanding of design principles to create clear and accurate visualisations, with an interest in learning about accessibility best practices
• Willingness to learn from peers: Open to feedback and guidance from senior team members to improve the quality of your visualisations
• Data quality assurance: Familiarity with data quality assessment techniques, such as data profiling and cleansing, with a willingness to learn more about improving data accuracy and consistency
• Data validation and linkage: Experience performing basic data validation checks and combining data from different sources, with guidance from senior team members
• Data cleansing and preparation: Experience in data preparation, including handling missing values and duplicates, with a focus on learning more advanced data cleansing techniques
• Communication of data limitations: Ability to discuss data limitations with guidance from others, helping stakeholders understand potential issues and make informed decisions
• Participating in peer reviews: Willingness to participate in peer reviews to improve data accuracy, with the support of more experienced team members
• Knowledge of statistical methods: Familiarity with common statistical techniques like hypothesis testing, regression analysis, and basic clustering, with an eagerness to learn how to choose the right methods for different projects
• Data analysis and interpretation: Experience using statistical software or programming languages for data analysis, with guidance in generating insights and sharing findings with both technical and non-technical audiences
• Willingness to learn new methodologies: Interest in exploring and applying new statistical techniques, with support from senior team members, to solve real-world problems and stay updated on emerging theories
• Stakeholder communication: Some experience working with different types of stakeholders, both technical and business-focused, with a focus on learning to manage expectations and contribute to productive discussions
• Willingness to engage in active and reactive communication: Comfortable sharing updates and responding to inquiries, with support from team members, to help maintain a collaborative working environment
• Interpretation of stakeholder needs: Ability to understand basic stakeholder requirements and help translate them into technical solutions, with guidance in bridging the gap between technical and non-technical individuals
• Presentation skills: Experience presenting data and insights, with a focus on learning how to simplify complex information for various audiences, including senior team members
• Problem-solving skills: Ability to apply logical thinking to break down simpler problems and contribute to generating solutions, with support from more experienced team members
• Decision-making and action-taking: Experience in making informed decisions and prioritising tasks, with guidance to take appropriate actions in resolving issues efficiently
• Adaptability and learning orientation: Willingness to adapt to new challenges and a strong desire to learn and improve continuously

Interest in automation: An interest in learning how to automate data management activities to streamline processes and improve accuracy (desirable)

• 30 days Holiday - we offer 30 days of paid annual leave + bank holidays
• Flexible Parental Leave - we offer flexible parental leave options
• Remote Working - we offer part time remote working for all our staff
• Paid counselling - we offer paid counselling as well as financial and legal advice
• Smart Tech scheme
• Cycle to work scheme
• individual benefits allowance which you can invest in a Health care cash plan or Pension plan
• optional social and wellbeing calendar of events