Data Analyst (Senior 4-7 Years)

Location: Amsterdam 2-3 times/week onsite. We are looking for an experienced Data Analyst who will play a key role in shaping the logistics of fulfilling customer orders at IKEA. The Data Analyst will be part of the Order Allocation & Network Optimization area, in the Fulfilment and Core Services domain. The team is cross-functional, builds models and does analysis about the performance of fulfillment logistics, with the perspective of balancing various trade-offs.

In addition, the team provides insights to business partners on system configurations and logistic process improvements at a global scale, in countries where IKEA is present. The Data Analyst will closely work with data scientists, data analysts, business owners and product owners in the area of article placement and configuration in a fulfilment network.

This will require: Developing analytical models to measure performance and identify trade-offs about the placement decision of articles in the fulfilment network to meet customer demand efficiently; Partnering with data scientists on translating complex fulfilment and network optimization challenges into actionable insights; Identify business opportunities to improve article accessibility, reduce unnecessary order splits, optimize transport flows, and increase network efficiency through data-driven analysis and experimentation; Communicating insights and recommendations to technical and non-technical audiences (e.g., global and local business), influencing decisions on article placement and fulfillment operations, as strategic and operational levels.

Day-to-day tasks: Perform data analysis to optimise article placement in the fulfilment network; Define and monitor KPIs for network performance and business impact; Collaborate with data scientists and business teams on analytical initiatives; Evaluate trade-offs between cost, operational efficiency, and customer satisfaction; Communicate insights and recommendations to stakeholders and decision-makers; Support decision makers at a granular level.

Desired knowledge, experience, competence, skills etc: The ideal candidate should possess strong analytical skills, business curiosity and proactive communication.

In particular: Knowledge and experience of advanced analytics, especially in fulfilment logistics and article/inventory network; Python and SQL skills for data analysis and exploration; Proficiency with Google Cloud Platform: BigQuery, JupyterLab, Looker Studio, etc.; Excellent communication skills, proactive attitude and critical thinking; Team spirit and ability to work in cross-functional teams with data scientist, data analysts and business partners.