Principal Data Scientist

World of Books Group; Greater London; On-site; GBP 80,000 - 110,000; Full time

Job summary

A global ecommerce company is seeking a Principal Data Scientist to lead advanced pricing optimization efforts. In this influential role, you will apply machine learning and causal inference to solve complex pricing problems while mentoring junior data scientists. Ideal candidates will have expertise in Python and SQL, alongside a strong statistical background for impactful decision-making. Join a mission-driven team focused on sustainable practices and be part of a dynamic culture driving real-world change.

Qualifications

• Deep experience applying data science in commercial environments, especially in pricing and ecommerce.
• Proven experience deploying and iterating on models in production.
• Ability to influence through expertise and communicate clearly with senior stakeholders.

Responsibilities

• Leading advanced pricing optimisation, elasticity modelling, and experimentation.
• Designing and evaluating A/B tests and quasi-experiments.
• Building and deploying production‑grade models with strong observability.
• Mentoring senior and mid-level data scientists.
• Advising stakeholders on trade‑offs between rigour and business value.
• Identifying future high-value data science use cases.

Skills

Deep experience applying data science in commercial environments

Expert Python

Strong SQL

Advanced knowledge of statistics

Advanced knowledge of ML

Causal inference

Job description

Posted Thursday 22 January 2026 at 01:00 | Expires Sunday 8 February 2026 at 00:59

At World of Books, we’re on a mission to become the Planet’s Bookstore — helping people read more while wasting less. As a certified B-Corp and a £200m+ global ecommerce business, data science sits at the heart of how we price millions of books sustainably and profitably.

We’re now looking for a Principal Data Scientist to play a critical technical leadership role in shaping how advanced modelling and experimentation are applied to pricing at scale.

The Role

This is a senior individual contributor role (no people management), focused on solving complex, high-impact pricing problems through experimentation, causal inference and applied machine learning.

You’ll work closely with our Data Science Manager, engineers and commercial leaders, acting as a technical authority and mentor while remaining hands‑on.

What You’ll Be Doing

• Leading advanced pricing optimisation, elasticity modelling and experimentation
• Designing and evaluating A/B tests, bandits and quasi-experiments
• Building and deploying production‑grade models with strong observability
• Setting practical standards for modelling, experimentation and DS workflows
• Mentoring senior and mid‑level data scientists through review and example
• Advising stakeholders on trade‑offs between rigour, speed and business value
• Identifying future high‑value data science use cases beyond pricing

What We’re Looking For

• Deep experience applying data science in commercial environments (pricing, ecommerce or marketplaces ideal)
• Expert Python and strong SQL
• Advanced knowledge of statistics, ML and causal inference
• Proven experience deploying and iterating on models in production
• Ability to influence through expertise and communicate clearly with senior stakeholders
• Pragmatic, outcome‑focused mindset with comfort in ambiguity

Why Join World of Books?

• Work on meaningful, planet‑positive problems at global scale
• A true Principal IC role with influence but no line management
• Partner closely with an experienced DS Manager who owns strategy and prioritisation
• Help shape how data science is practised in a growing, evolving organisation
• Be part of a mission‑driven, collaborative and inclusive culture

Interested?

If you’re a senior data scientist who thrives on complex problems, hands‑on technical leadership and real‑world impact — we’d love to hear from you.

World of Books is proud to be an equal opportunities employer and is committed to building a diverse and inclusive team.