Ralph Lauren Data Scientist

Ralph Lauren; City Of London; On-site; GBP 50,000 - 70,000; Full time

Job summary

A leading lifestyle brand in the UK is looking for an experienced Data Scientist to enhance customer experiences through predictive modeling and data analysis. The role involves collaboration with marketing and engineering teams to ensure effective data-driven decisions. Ideal candidates will have strong Python skills and experience with machine learning techniques.

Qualifications

• Experience in Customer Marketing Data Science with applied statistics and machine learning techniques.
• Familiarity with cloud platforms and ML Ops.
• Global or multi-regional experience is a plus.

Responsibilities

• Build predictive models to forecast customer behavior.
• Create customer segmentation using behavioral and demographic data.
• Collaborate on methods to measure CRM effectiveness.

Skills

Customer Marketing Data Science

Applied statistics

Machine learning techniques

Proficiency in Python

Cloud platforms (GCP, AWS, Azure)

Communication skills

Tools

pandas

numpy

scikit-learn

tensorflow

pytorch

Dataiku

Databricks

Job description

Company Description

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.

Position Overview

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.

Essential Duties & Responsibilities

• 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 channels.
• Create sophisticated customer segmentation using behavioural, transactional, and demographic data.
• Collaborate on design of test & learn methods to measure CRM initiatives' effectiveness.
• Monitor performance to ensure models perform as effectively as possible for continuous improvement.
• Communicate algorithmic solutions in a clear, understandable way.
• Leverage data visualisation techniques and tools to effectively demonstrate patterns, outliers and exceptional conditions in the data.
• Collaborate with CRM and regional marketing teams to align with campaign goals and customer segmentation strategies.
• Partner with engineering and data teams to ensure scalable solutions.
• Continuously monitor and improve model performance using data insights and feedback.

Experience, Skills & Knowledge

• 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 skills.
• Experience in a global or multi-regional context is a plus.