Senior Data Analyst  

1. Analysis and Delivery for B2B Customers

• Leverage a variety of data analysis techniques to derive valuable insights from large FMCG e-commerce datasets.
• Collaborate with cross-functional teams to comprehend client requirements and deliver actionable insights in a timely manner, including client reports, raw data, or dashboards.
• Translate complex data findings into clear, concise reports or presentations for both internal and external stakeholders.

2. Delivering Client Market Insight Dashboards

• Assist in the development and deployment of client market insight dashboards, working alongside the Product Delivery PIC.
• Collaborate with the analytics product development team to ensure data visualizations and dashboards are accurate, reliable, and relevant; propose improvements or recommendations as necessary.

3. Day-to-Day Analysis and Strategy

• Work closely with internal teams to pinpoint optimization opportunities and enhance business strategies (with a focus on Compas Enabler Services).
• Contribute to the development and execution of data-driven strategies aimed at business growth and improved client satisfaction.
• Stay informed on industry best practices and emerging technologies in data analysis and market insights.
• Perform data validation for reports and dashboards, supporting data issue resolution, data mapping, and segmentation.

• Bachelor’s degree with min. 4 years of proven experience as a Data Analyst, with preference for experience in the FMCG or e-commerce sectors.
• Proficiency in data analysis and visualization tools, including SQL (BigQuery), Python, Regex, Looker/GDS, Tableau, or similar platforms.
• Strong analytical and problem-solving skills, with a demonstrated ability to extract actionable insights from complex datasets.
• Excellent communication skills for presenting findings and ability to interpret, simplify, clearly convey data findings and recommendations for both technical and non-technical audiences, adapting insights to different stakeholders needs.
• Ability to work independently in a fast-paced environment.
• Skilled in defining requirements and refining them for deliverable tasks.
• Knowledge of best practices in data analysis methodologies, such as sampling, outlier detection, and distribution analysis.