Data Scientist

Ralph Lauren; Greater London; On-site; GBP 60,000 - 80,000; Full time

Job summary

A global fashion brand is seeking an experienced Data Scientist to analyze vast amounts of customer data. Your focus will be on delivering data-driven insights to enhance customer experiences. The ideal candidate should have a strong background in machine learning, Python, and applied statistics, with responsibilities including building predictive models and customer segmentation. This position offers opportunities for collaboration across various teams to drive business results.

Qualifications

• Relevant experience in Customer Marketing Data Science including applied statistics and machine learning techniques.
• Proficiency in Python with familiarity to ML libraries.
• Knowledge of cloud platforms (GCP, AWS, Azure) is beneficial.

Responsibilities

• Build predictive models to forecast customer behavior.
• Create customer segmentation using behavioral, transactional, and demographic data.
• Collaborate on CRM initiatives' effectiveness and model improvement.

Skills

Applied statistics

Machine learning techniques

Python programming

Data visualization

Excellent communication skills

Tools

pandas

numpy

scikit-learn

tensorflow

pytorch

Dataiku

Databricks

Job description

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