The Data Analyst will be responsible for collecting, analysing, and interpreting large datasets to identify trends, patterns, and insights that support strategic decision-making. The ideal candidate will have strong analytical skills, attention to detail, and the ability to present findings in a clear and impactful manner to stakeholders across the business.
Key Responsibilities
Gather, clean, and analyse data from various sources to deliver actionable insights.
Design and develop dashboards, reports, and visualizations using tools like Excel, Power BI, Tableau, or similar platforms.
Collaborate with cross-functional teams (e.g., Marketing, Operations, Finance) to understand business needs and provide data-driven recommendations.
Identify key performance metrics (KPIs) and monitor performance against business goals.
Use statistical methods and data modelling techniques to analyse trends and forecasts.
Automate repetitive data processes to improve efficiency and accuracy.
Present findings and insights clearly to both technical and non-technical stakeholders.
Support data quality initiatives by identifying and addressing inconsistencies or inaccuracies.
Required Skills and Experience
Proficiency in data visualization tools (e.g., Tableau, Power BI, Looker) and Excel.
Strong SQL skills for querying and analysing data from relational databases.
Experience with statistical analysis tools (e.g., Python, R, SPSS) is a plus.
Solid understanding of data structures, data cleaning, and transformation techniques.
Exceptional problem-solving skills and attention to detail.
Ability to communicate complex information in a simple, clear, and compelling way.
Key Attributes
Proactive, detail-oriented, and highly organized.
Strong analytical mindset with a passion for solving complex business problems.
Ability to work independently and collaboratively in a fast-paced environment.
Excellent communication skills with the ability to explain technical concepts to non-technical audiences.
Benefits
Competitive salary and performance-based incentives.
Opportunity to work in a collaborative, data-driven environment.
Access to professional development and training opportunities.
Flexible working arrangements (remote or hybrid options available).
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