Data Science Manager

Ralph Lauren; Greater London; On-site; GBP 70,000 - 90,000; Full time

Job summary

A global fashion retailer is seeking a passionate Data Scientist Manager to lead personalization efforts within its CRM ecosystem. The ideal candidate will develop predictive models and recommendation systems to enhance customer engagement across markets. Responsibilities include leading machine learning solutions development, optimizing recommendation engines, and collaborating with marketing and engineering teams. Proficiency in Python and experience with ML Ops are essential for this role.

Qualifications

• Experience in machine learning and recommendation systems.
• Understanding of neural networks and embedding techniques.
• Familiarity with cloud platforms and ML Ops.

Responsibilities

• Lead development of machine learning solutions for CRM personalization.
• Build and optimize recommendation engines using advanced features.
• Collaborate with teams to align with campaign goals.

Skills

Machine learning solutions

Recommendation systems

Deep learning architectures

Python proficiency

Excellent communication

Tools

TensorFlow

PyTorch

Dataiku

GCP

AWS

Azure

Job description

Position Overview

We’re looking for a passionate and experienced Data Scientist Manager to lead personalization efforts within Ralph Lauren’s CRM ecosystem. You’ll develop predictive models and recommendation systems that enhance customer engagement across global markets.

Essential Duties & Responsibilities

• Lead development of machine learning solutions for CRM personalization.
• Build and optimize recommendation engines using neural networks and deep learning, incorporating product embeddings and other advanced features to improve relevance and performance.
• Collaborate with CRM and regional marketing teams to align with campaign goals and customer segmentation strategies.
• Own the full ML lifecycle—from model design to deployment and monitoring.
• Partner with engineering and data teams to ensure scalable solutions.
• Continuously monitor and improve model performance using data insights and feedback.

Experience, Skills & Knowledge

• Proven experience in machine learning, particularly in recommendation systems and deep learning architectures.
• Strong understanding of two-tower neural networks, embedding techniques, and ranking models.
• Proficiency in Python with familiarity to ML libraries such as pandas, numpy, scipy, scikit-learn, tensorflow, pytorch.
• Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku.
• Experience with ML Ops, including model deployment, monitoring, and retraining pipelines.
• Ability to work cross-functionally with marketing, CRM, and engineering teams.
• Excellent communication and stakeholder management skills.
• Experience in a global or multi-regional context is a plus.