Data analyst

Data Analyst - Cardiff 
Hybrid working 3 days onsite p/week, insite parking available
We are looking for an experienced Data Analyst who can understand, interpret, and predict patterns across our clients business. They are looking for someone who can use those data-driven insights to enhance their business practices in order to achieve company goals/KPI’s.
Expert in MS Excel
Statistical, mathematical, or financial (one is essential – you should demonstrate a sound background)
SQL experience (coding)
Experience with data visualisation tools (Power Bi, Tableau etc)
Familiarity with data modelling, data warehousing, ETL process (foundational) – ideally someone with good experience in all 3.
Perform data analysis and apply statistical techniques to identify trends, patterns, correlations, and insights.
• Create, update and maintain regular Management Information and regulatory reports and dashboards.
• Interpret data and present findings to stakeholders in a clear and concise manner through reports, visualizations, and presentations.
• Develop data models, dashboards, and reports to track key performance indicators (KPIs) and provide actionable insights.
• Collect, cleanse, and organize large and complex data sets from various sources.
• Collaborate with cross-functional teams to identify data requirements and support data-driven decision-making processes.
• Identify data quality issues and work with relevant teams to resolve them, ensuring accuracy and reliability of data
A relevant professional qualification in Data Science, Statistics, Mathematics, or a related field is desirable
• Proven experience working as a Data Analyst or in a similar role

Strong analytical skills with the ability to collect, organise, analyse, and interpret large and complex data sets.
• Proficiency in data management and analysis tools and programming languages such as SQL, Python, R, or SAS.
• Experience with data visualisation tools such as Power BI (preferred), Tableau, or QlikView.
• Solid understanding of statistical methods and techniques for data analysis.
• Familiarity with data modelling, data warehousing, and ETL processes.