About the Role
We are seeking a highly skilled and motivated Data Analyst to join our team. As a Data Analyst, you will be responsible for collecting, analysing, and interpreting data from various sources to provide actionable insights and support data-driven decision-making. You will work closely with stakeholders across the organisation to understand their requirements and deliver valuable solutions. The ideal candidate should possess a strong background in data analysis, statistical modeling, programming in Python or R, dashboard development, and business intelligence tools.
Requirements
 Bachelor's or Master's degree in a relevant field (e.g., Computer Science, Statistics, Mathematics, Business Analytics).
Proven experience as a Data Analyst or similar role with a focus on data analysis, mathematical modelling, and business intelligence.
Proficiency in programming languages such as Python or R, and experience with data manipulation libraries like Pandas or dplyr.
Strong mathematical and statistical skills to design, implement, and interpret advanced models.
Experience in data visualisation tools like Tableau, Power BI, or similar platforms to create impactful dashboards and reports.
Knowledge of SQL for data retrieval and manipulation from databases.
 Strong analytical thinking, problem-solving, and attention to detail.
 Excellent communication and presentation skills to effectively convey complex insights to non-technical stakeholders.
 Ability to work both independently and collaboratively in a team-oriented environment.
  Strong organisational and time-management skills to manage multiple projects simultaneously.
If you possess a passion for data-driven decision-making and enjoy transforming raw data into valuable insights, this role offers an exciting opportunity to make a significant impact on our organisation’s success. We look forward to welcoming a highly motivated and capable Data Analyst to our team.
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Key Responsibilities:
1. Data Analysis and Interpretation: Collect, clean, and analyse large datasets to extract meaningful information and insights. Identify trends, patterns, and correlations to support business objectives.
2. Mathematical Modeling: Develop and implement mathematical and statistical models to solve complex business problems, such as forecasting, optimisation, and simulation.
3. Programming: Utilize Python or R to write efficient and reusable code for data manipulation, statistical analysis, and model implementation.
4. Dashboard Creation: Design and build interactive and visually appealing dashboards using data visualisation tools like Tableau, Power BI, or similar platforms. Present data in a concise and user-friendly manner for easy consumption by stakeholders.
5. Business Intelligence: Utilize business intelligence tools to create reports, data visualisations, and interactive dashboards to enable data-driven decision-making across the organisation.
6. Data Mining and Cleansing: Identify relevant data sources, extract data, and ensure data quality by performing data cleansing and validation procedures.
7. Collaborate with Stakeholders: Work closely with business leaders, department heads, and other team members to understand their data needs, answer ad-hoc queries, and provide analytical support.
8. Insights and Recommendations: Translate complex analytical findings into actionable insights and present them to non-technical stakeholders in a clear and understandable manner.
9. Continuous Improvement: Stay updated with the latest trends and advancements in data analysis, machine learning, and business intelligence technologies. Suggest and implement improvements to existing processes and methodologies.