The position can be based in London, Paris or Amsterdam.

Mission and purpose:

The Head of Commercial Data Analytics, EMEA, will spearhead the development of a best-in-class commercial analytics practice to transform WFS’s Commercial data-driven decision-making in the EMEAA region. This strategic role will focus on harnessing internal and external data to deliver predictive and prescriptive insights that optimize sales, pricing, commercial performance and contract strategies, particularly in response to competitive pressures. The role will establish a scalable analytics framework, integrate cutting-edge AI and machine learning capabilities, and drive customer-centric strategies through advanced market segmentation and loyalty modelling, enabling WFS to maintain its competitive edge in the global air cargo logistics market.

Main responsibilities:

• Data Strategy and Governance: Lead a comprehensive review and restructuring of internal data sources (e.g., CRM, ERP) to ensure data quality, consistency, and accessibility. Seek to integrate new and relevant external data sources (e.g., market intelligence, competitor data) to enhance strategic insights, particularly for the purposes of creating insights into competitive positioning.  
• Advanced Analytics Platform: Design and deploy a state-of-the-art commercial analytics dashboard, incorporating real-time tracking of key performance indicators (e.g., contract win/loss rates, pipeline velocity, pricing trends, commercial performance benchmarking and customer lifetime value) with predictive analytics capabilities for scalability across EMEA.  
• Ad-Hoc Strategic Analyses: Deliver an adhoc reporting capability designed to support demand for critical timebound guidance relating to pricing optimization, contract bundling, and client incentive strategies, ensuring WFS remains competitive in client negotiations.  
• AI-Driven Analytics Integration: Establish best practices for incorporating AI and machine learning into the analytics practice, including automated pricing recommendations and other repetitive commercial processes (e.g., real-time contract monitoring, pipeline analyses improving operational efficiency and enabling proactive decision-making in response to competitive pressures.
• Market Segmentation and Customer Value Modelling: Develop a robust market segmentation framework and customer value/loyalty model to identify high-value airline clients, tailor service offerings, and strengthen retention strategies in response to competitive pressures.  
• Process and Scalability Framework: Define standardized workflows for data collection, validation, and reporting to ensure consistency and scalability, embedding governance protocols to support future advanced analytics initiatives (e.g., yield optimization, capacity forecasting).  
• Stakeholder Engagement and Change Management: Collaborate with commercial, IT, and finance teams to align analytics outputs with business priorities, driving adoption of data-driven decision-making through tailored training and stakeholder workshops.  
• Future-State Analytics Roadmap: Develop a 3-year roadmap for advanced analytics capabilities, including contract profitability analysis, demand-capacity optimization, and ancillary revenue modelling, to position WFS as a data-driven leader in the air cargo handling sector.

Qualifications/skills/training/experience:

• Advanced degree in a STEM field (e.g., Data Science, Statistics, Computer Science, Mathematics, or related) or equivalent experience; MBA or business-related master’s degree is a plus.  
• Minimum of 7 years of experience in data analytics, business intelligence, or data science, with at least 3 years in a similar role within logistics, aviation, or a related industry.  
• Expertise in advanced data visualization and dashboard development using tools such as Tableau, Power BI, or Qlik, with a focus on real-time, interactive reporting.  
• Advanced proficiency in data manipulation, statistical analysis, and machine learning using SQL, Python, R, or equivalent tools; familiarity with cloud-based platforms (e.g., AWS, Azure) is highly desirable.  
• Proven experience in integrating and synthesizing diverse internal and external data sources to deliver actionable insights.  
• Hands-on experience with AI-driven analytics tools and frameworks (e.g., TensorFlow, PyTorch, or similar) and their application in commercial contexts.  
• Strong understanding of CRM (e.g., Salesforce, MS Dynamics) and ERP systems, with experience leveraging these for commercial insights.  
• Exceptional communication and stakeholder management skills, with a track record of translating complex analytics into strategic recommendations for C-suite and non-technical audiences.  
• Demonstrated ability to lead cross-functional teams and drive organizational change in data-driven decision-making.

People values:

Safety
Champion a data-driven approach to operational safety by integrating safety-related metrics (e.g., incident rates, compliance adherence) into the commercial analytics framework.    Customer Focus
Develop analytics that prioritize customer needs, such as tailored pricing models and loyalty programs, to strengthen relationships with airline clients and counter competitive offerings.    
Respect
Foster an inclusive analytics culture by engaging diverse stakeholder perspectives and ensuring transparent, ethical use of data in decision-making processes.    
Excellence
Drive continuous improvement in analytics practices by adopting cutting-edge tools, benchmarking against industry leaders, and delivering high-quality, actionable insights.    
Teamwork
Build collaborative partnerships across commercial, IT, and finance teams to integrate data systems and align analytics with WFS’s strategic goals, promoting a unified approach to data-driven success.

Aptitudes:

• Strategic and analytical mindset with a proven ability to solve complex problems and translate data into business value.  
• Exceptional leadership and influencing skills to drive organizational change and foster a data-driven culture.       
• Proactive approach to identifying innovative analytics solutions, including AI and market segmentation strategies.  
• Strong organizational and project management skills to prioritize initiatives and meet strategic deadlines in a fast-paced environment.