• Develop and maintain an accurate and up-to-date data model to support business analyses and strategic decisions.
• Analyze and interpret customer data to identify trends, behaviors, and market opportunities, such as predicting churn and identifying potential up-selling and cross-selling opportunities.
• Improve current ongoing analyses on segmentation, churn, and customer base propensities by researching new analysis methods and implementing them for optimal performance.
• Research and analyze new ideas to optimize our customer studies and processes.
• Actively collaborate with various stakeholders to translate complex insights into concrete recommendations for retail teams and ensure alignment with business strategies.
• Monitor marketing campaign performance and provide recommendations to optimize their effectiveness and define and monitor actions on the customer base to increase its value and loyalty, optimizing business margins in line with company targets.
  

• Excellent knowledge of data analysis techniques and at least one programming language (e.g. Python) and SQL to extract value from data.
• Advanced skills in Excel and BI tools (Power BI) to effectively visualize and communicate business insights.
• Ability to set up a business case to evaluate the return of an action on a set of customers and their value evolution over
• Ability to bridge the gap between technical and non-technical stakeholders, ensuring effective and inclusive communication.
• Ability to translate complex insights into clear, concise, and actionable recommendations, tailoring the message to the target audience.
• Ability to tackle challenges related to data quality, analysis, and technical difficulties, finding innovative and pragmatic solutions.
• Curiosity and continuous learning.
• Ability to critically evaluate data, identify biases, and ensure reliable and robust insights.
• Communicate results clearly, simply, and effectively.
• Master's degree in a quantitative field (Mathematics, Statistics, Computer Science, Data Science, or similar).
• A Ph.D. is considered a strong plus.
• 4-8 years of professional experience as a Data Analyst or Data Scientist
• Experience in managing and analyzing pricing strategies, with a particular focus on margin dynamics, price setting, and churn management.
• Experience in managing data-driven projects on customer centricity.
• Advanced experience in Excel and BI and Data Visualization tools (e.g., Power BI).
• Advanced experience with SQL.
• Experience in scripting languages or statistical tools (Python, R, SPSS, ...) and major machine learning libraries is considered a strong plus.
• Experience with Git is considered a strong plus.

• Permanent employment contract
• Health insurance and supplementary pension fund
• Life-long learning
• Development and empowerment paths
• Corporate welfare for better work-life balance (parenting support, daycare, extra parental leave etc…)
• Benefits with dedicated offers and conventions (meal vouchers, travel, transport, sports, culture, energy etc...)