Senior Data Analyst, Merchandising Analytics (EU)

Circle K Stores Inc.; Dublin; Hybrid; EUR 65,000 - 90,000; Full time

Job summary

Circle K Stores Inc. in Dublin, Ireland is seeking a Senior Data Analyst to support its European Merchandising Analytics team. You will translate business questions into analytical requirements and work across categories and markets.

You will lead analytics projects end-to-end, develop scalable dashboards and reporting, and apply advanced techniques such as forecasting and hypothesis testing. Collaboration with data engineering and business stakeholders across Europe is essential.

Qualifications

• 3+ years of analytics, data science, BI or related experience.
• Experience in retail, merchandising analytics, pricing/promotions or customer behavior.
• Proficient with SQL and Python/PySpark; Databricks/Azure experience is a plus.
• Ability to communicate complex findings to non-technical audiences.

Responsibilities

• Partner with European Merchandising, Category and other business teams to understand priorities and translate them into analytical requirements and KPIs.
• Lead analytics projects from problem definition through data exploration, analysis, recommendations and stakeholder communication.
• Develop scalable dashboards and reporting solutions (Power BI or similar) for performance monitoring.
• Design and evaluate experiments and pilots, including test design and interpretation of results.
• Collaborate with Data Engineering and other analytics teams to improve data quality and reusable capabilities.

Skills

SQL

Python

Stakeholder management

Analytical thinking

English communication

Education

Master's or Bachelor's degree in a relevant field

Tools

Databricks

Azure

Power BI

PySpark

Job description

Circle K Stores Inc. in Dublin, Ireland is seeking a Senior Data Analyst to support its European Merchandising Analytics team. You will translate business questions into analytical requirements and work across categories and markets.

You will lead analytics projects end-to-end, develop scalable dashboards and reporting, and apply advanced techniques such as forecasting and hypothesis testing. Collaboration with data engineering and business stakeholders across Europe is essential.