Purpose and Scope

The Data & AI Analyst role is positioned to tap on the vast amounts of data available to better guide the organisation in optimising its operational and business processes. The role will reside within the Digital Integration & Business Processes Unit and will work on cross-functional projects.

Someone without experience is welcome. Candidates will be expected to share about projects previously delivered.

Key Roles and Responsibilities

• Work with stakeholders to propose, develop and maintain automated data collection systems and pipelines across reporting lines.
• Provide stakeholders with accurate and relevant information through data-driven reports, visualizations, and presentations.
• Assist to identify and solve complex business problems by interpreting data trends and patterns.
• Develop statistical models and forecasts to support business planning.
• Integrate and leverage AI where relevant to extract and interpret actionable business insights.
• Continuously evaluate and refine existing data processes and methodologies to enhance data quality, integrity, and operational efficiency.

Qualifications & Experience

• Bachelor’s degree in a quantitative field such as Data Science, Business Analytics, Statistics, Mathematics, Computer Science, Engineering, Economics, or related fields.
• Demonstrable experience with data visualization tools like Power BI, Tableau, or matplotlib/seaborn in Python.
• Experience in data cleaning, transformation, and integration.
• Experience working in cross-functional teams and collaborating with stakeholders from different departments.
• Proficiency in analysing large datasets to extract meaningful insights with Python, Excel and/or SQL
• Proficiency in analysing large datasets to extract meaningful insights with Excel, Python and/or SQL
• Experience with Power Query and Power Automate can be advantageous
• Knowledge of database system and data-warehousing concepts can be advantageous.
• Knowledge of Machine Learning and Artificial Intelligence concepts can be advantageous.

Skills / Competencies & Preferred Characteristics

• Understanding of statistical methods and concepts such as hypothesis testing, regression analysis, clustering, and classification techniques.
• Ability to use statistical methods and tools to interpret data and solve analytical problems.
• Ability to understand business requirements, translate them into analytical tasks, and provide actionable insights to stakeholders.
• Capability to identify problems and develop creative solutions using data-driven techniques.
• Effective communication of findings through reports, presentations, and visualizations to both technical and non-technical audiences.
• Thoroughness in data analysis and ensuring data quality and accuracy in findings and reports.