Data Analyst Fulfilment & Network Optimization

Huxley; Amsterdam; Sur place; EUR 55 000 - 75 000; Plein temps

Résumé du poste

Huxley is seeking an experienced Data Analyst to shape the logistics of fulfilling customer orders in a global retail environment. You will work within the Fulfilment and Core Services domain, focusing on article placement and network optimization across the fulfilment network.

You will collaborate with Data Scientists, Business Owners, and Product Owners to translate complex challenges into data-driven insights and improvements that enhance performance and reduce unnecessary order splits.

Qualifications

• Experience with advanced analytics in fulfilment/logistics or inventory networks.
• Strong Python and SQL skills for data analysis and exploration.
• Proactive mindset with excellent communication and collaboration abilities.

Responsabilités

• Develop analytical models to measure performance and trade-offs in article placement within the fulfilment network.
• Partner with Data Scientists to translate challenges into actionable insights.
• Identify opportunities to improve article accessibility, optimize transport flows and increase network efficiency.
• Present insights and recommendations to technical and non-technical stakeholders at strategic and operational levels.

Connaissances

Python

SQL

Communication

Cross-functional collaboration

Critical thinking

Outils

BigQuery

JupyterLab

Looker Studio

Description du poste

Data Analyst (Fulfilment & Network Optimization)

Background

We are looking for an experienced Data Analyst who will play a key role in shaping the logistics of fulfilling customer orders in a global retail environment. The Data Analyst will be part of the Order Allocation & Network Optimization area within the Fulfilment and Core Services domain. The team is cross-functional and focuses on building models and performing analyses on fulfilment logistics performance, balancing various trade-offs. The team also provides insights to business stakeholders regarding system configurations and logistics process improvements on a global scale.

Assignment Scope

The Data Analyst will work closely with Data Scientists, Data Analysts, Business Owners, and Product Owners in the area of article placement and configuration within the fulfilment network.

Responsibilities

• Developing analytical models to measure performance and identify trade-offs related to article placement decisions within the fulfilment network.
• Partnering with Data Scientists to translate complex fulfilment and network optimization challenges into actionable insights.
• Identifying opportunities to improve article accessibility, reduce unnecessary order splits, optimize transport flows, and increase network efficiency through data-driven analysis and experimentation.
• Presenting insights and recommendations to both technical and non-technical stakeholders at strategic and operational levels.

Day-to-Day Tasks

• Perform data analysis to optimize article placement within the fulfilment network.
• Define and monitor KPIs related to 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-making at a detailed operational level.

Skills & Experience

• Knowledge and experience in advanced analytics, preferably within fulfilment logistics and inventory/article network optimization.
• Strong Python and SQL skills for data analysis and data exploration.
• Experience with Google Cloud Platform, including:
  • BigQuery
  • JupyterLab
  • Looker Studio
• Excellent communication skills.
• Proactive mindset and critical thinking abilities.
• Strong collaboration skills and experience working in cross-functional teams.

Top 3 Priorities

• Python and SQL skills for data analysis and exploration.
• Excellent communication skills, proactive attitude, and critical thinking.
• Ability to work effectively in cross-functional teams.