Kering Data Scientist

About Kering

Kering is a global luxury group renowned for nurturing some of the world’s most influential Houses in fashion, leather goods, jewelry, and eyewear, including Gucci, Saint Laurent, Bottega Veneta, Balenciaga, and Boucheron. As an employer, Kering offers a distinctive environment where creative excellence, entrepreneurial spirit, and long-term sustainability converge. The Group empowers its talents to shape the future of luxury through innovation, craftsmanship, and responsible business practices. With an international culture grounded in diversity, inclusion, and shared ambition, Kering provides meaningful career opportunities for professionals seeking to contribute to exceptional brands while advancing a more sustainable and imaginative luxury industry.

Role & Responsibilities

• Lead end-to-end marketing effectiveness measurement projects across multiple Houses and markets, managing the complete analytics lifecycle from project scoping and data collection through modeling, results interpretation, and delivery of actionable recommendations
• Design, develop, and continuously enhance statistical, econometric, and Marketing Mix Modeling (MMM) models to quantify the impact and incremental contribution of various marketing levers on key business performance indicators including sales, traffic, engagement, and ROI
• Produce analyses and insights that are directly actionable by Media, Marketing, and CRM teams, including ROAS measurement, channel contribution attribution, saturation curve analysis, investment scenario modeling, and budget allocation optimization recommendations
• Develop robust, scalable, and standardized methodologies that can be applied across the Group while accommodating House-specific, market-specific, and data availability constraints to ensure analytical consistency and business relevance
• Collaborate closely with Kering Media, Marketing, CRM, and Data teams, the individual Houses, and external partners to ensure the quality, reliability, and usability of data integrated within analytical models and frameworks
• Ensure the quality and robustness of analytical output by critically challenging source data, conducting comprehensive sensitivity analyses, and transparently assessing uncertainty levels and limitations associated with developed models
• Present findings and recommendations to both technical and business stakeholders, facilitate decision-making processes, and drive stakeholder adoption of insights to maximize business impact and inform strategic investment allocation

Qualifications

• Bachelor's degree in Data Science, Statistics, Econometrics, Applied Mathematics, Quantitative Economics, or a related quantitative field
• Strong foundation in statistical and econometric modeling, including regression techniques, time-series analysis, Bayesian methodologies, model validation frameworks, and uncertainty quantification
• Solid mastery of key Marketing Mix Modeling (MMM) concepts including adstock effects, saturation curves, baseline decomposition, control variables, ROAS calculation, and response curve analysis
• Expert-level proficiency in Python, SQL, and Git for developing, industrializing, and maintaining robust analytical models and production-grade solutions
• Demonstrated ability to collect, explore, validate, and reconcile data from diverse sources; identify data anomalies; and critically assess the reliability of model outputs and analytical findings
• Practical experience integrating Artificial Intelligence tools and best practices into analytical workflows to enhance productivity and improve the quality of deliverables
• Ability to understand, challenge, and support complex business requirements within international, multidisciplinary environments with competing stakeholder priorities
• Strong communication and collaboration skills, with demonstrated ability to engage effectively with both technical specialists and non-technical business stakeholders
• Rigorous analytical and synthesis capabilities, enabling rapid identification of key business challenges and development of contextually relevant solutions
• Demonstrated curiosity, initiative, and continuous learning orientation, with willingness to share knowledge and actively contribute to collective team success

Skills

Experience

3 to 5 years of professional experience in Data Science, Econometrics, or Marketing Analytics, with proven expertise in marketing effectiveness measurement through Marketing Mix Modeling (MMM) projects and multi-channel marketing attribution. Demonstrated track record of transforming complex datasets into clear, actionable recommendations for executive and operational stakeholders. Experience collaborating with cross-functional teams across marketing, media, CRM, and data organizations in matrix-driven environments is highly valued.

Education

Bachelor's degree in Data Science, Statistics, Econometrics, Applied Mathematics, Quantitative Economics, or a closely related quantitative discipline.

Workplace

Culture

Kering fosters a dynamic, purpose-driven culture where creativity, entrepreneurship, and collaboration support the distinct identities of its luxury Houses. As an employer, the Group places strong emphasis on sustainability, diversity, and talent development, encouraging people to innovate responsibly while contributing to the future of modern luxury.

About Cerulean

Cerulean is the definitive career portal for the global luxury industry. We match exceptional professionals with exclusive opportunities at the world's most prestigious brands. From haute couture and fine watchmaking to prestige beauty, hospitality, and boutique retail, Cerulean centralises luxury employment to help you find the career for which you were destined.