Data Scientist

Ralph Lauren Corporation (NYSE:RL) is a global leader in the design, marketing and distribution of premium lifestyle products in five categories: apparel, accessories, home, fragrances, and hospitality. For more than 50 years, Ralph Lauren's reputation and distinctive image have been consistently developed across an expanding number of products, brands and international markets. The Company's brand names, which include Ralph Lauren, Ralph Lauren Collection, Ralph Lauren Purple Label, Polo Ralph Lauren, Double RL, Lauren Ralph Lauren, Polo Ralph Lauren Children, Chaps, among others, constitute one of the world's most widely recognized families of consumer brands.At Ralph Lauren, we unite and inspire the communities within our company as well as those in which we serve by amplifying voices and perspectives to create a culture of belonging, ensuring inclusion, and fairness for all. We foster a culture of inclusion through: Talent, Education & Communication, Employee Groups and Celebration.,We are seeking for an experienced, passionate and highly motivated Data Scientist who will help us discover the information hidden in vast amounts of customer data, and help us make data driven decisions to deliver better products, service and relevance to our customers.,Build predictive models to forecast customer behaviour, including purchase patterns, identification of life events and influence on purchase mission to enhance personalized customer experiences across all channelsCreate sophisticated customer segmentation using behavioural, transactional, and demographic dataCollaborate on design of test & learn methods to measure CRM initiatives' effectivenessMonitor performance to ensure models perform as effectively as possible for continuous improvementCommunicate algorithmic solutions in a clear, understandable way. Leverage data visualisation techniques and tools to effectively demonstrate patterns, outliers and exceptional conditions in the dataCollaborate with CRM and regional marketing teams to align with campaign goals and customer segmentation strategiesPartner with engineering and data teams to ensure scalable solutions.Continuously monitor and improve model performance using data insights and feedback,Relevant experience in Customer Marketing Data Science including applied statistics and machine learning techniques (supervised and unsupervised learning, natural language processing, Bayesian statistics, time-series forecasting, collaborative filtering etc)Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch)Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku, Databricks.Experience with ML Ops, including model deployment, monitoring, and retraining pipelines.Ability to work cross-functionally with marketing, CRM, and engineering teams.Excellent communication skillsExperience in a global or multi-regional context is a plus