Senior Applied Data Scientist (Retail)

TL;DR

Senior Applied Data Scientist (Data Science/Retail): Building and implementing complex models and applications to derive actionable insights for retail clients with an accent on statistical modelling and machine learning. Focus on solving challenging problems in category management and delivering measurable value through scalable data solutions.

Location: London (flexible working options discussed during hiring process)

Company

Global leader in Customer Data Science partnering with the world’s most ambitious retailers and brands to put the customer at the heart of every decision.

What you will do

• Implement, support, and develop complex models and applications to solve retail challenges.
• Distill complex problems into meaningful, actionable insights using cutting-edge ML techniques.
• Collaborate with client leadership to build re-usable, scalable solutions that deliver measurable value.
• Drive change and redefine how organizations harness data to improve customer outcomes.
• Bridge the gap between technical implementation and real-world business impact.

Requirements

• Degree in Statistics, Mathematics, Physics, Economics, or a related quantitative field.
• Strong programming skills in Python and SQL (essential).
• Proven experience in statistical modelling and applying data science solutions to real client problems.
• Experience with version control tools such as GIT.
• Project Management and/or Team Leadership experience.
• Strong communication skills to explain complex concepts to non-technical audiences.

Nice to have

• Experience with PySpark.
• Background in retail analytics, specifically exposure to Category Management.

Culture & Benefits

• Comprehensive rewards package typical of a leading technology company.
• Personal flexibility, including flexible working hours and your birthday off.
• Environment combining cutting-edge technology investment with a nimble, small-business feel.
• Strong commitment to diversity and inclusion with active employee networks.