Data Scientist - Consumer Behaviour

London Source: WhatJobs

£45,000–£60,000

Data Scientist - Consumer Behaviour

Central London / Hybrid - 3 days per week in the office (Tuesday to Thursday)

Salary range £45,000 - £60,000 depending on skills & experience

Ref: J13181

A fantastic opportunity for a Data Scientist looking for the opportunity to work on genuinely interesting problems, apply rigorous statistical thinking to large-scale behavioural data and have a real impact. This is a chance to join a small, high-performing Data Science team where you'll have significant exposure to interesting projects, experienced colleagues and real client challenges.

Working for one of the world's largest consumer behavioural data companies, providing deterministic behavioural data to many of the world's leading brands and platforms, including Google, Meta, Netflix and the BBC.

The Data Science team works with billions of consented consumer events across search, browsing, AI, social, retail, web, app and purchase activity, turning complex data into findings that clients can act on.

You'll be defining cohorts, choosing appropriate statistical approaches, investigating potential sources of bias and communicating your conclusions clearly. You'll also have the opportunity to contribute to the data products and pipelines that underpin the organisation's behavioural datasets and client reporting.

The Role:

Work with large-scale behavioural datasets covering consumer activity across multiple platforms
Define cohorts and datasets using SQL, including complex aggregations, CTEs and window functions
Apply statistical methods including hypothesis testing, confidence intervals and experimental analysis
Work with causal inference techniques such as A/B testing, difference-in-differences and matching
Investigate selection bias, confounding and other factors that could affect the validity of results
Develop and maintain data aggregation pipelines and datasets used across the business
Contribute to PII detection and client reporting processes
Validate analytical results against source data and investigate unexpected findings
Write clear, maintainable Python code that can be understood and reused by others
Work collaboratively through GitHub, pull requests and code reviews
Present findings, methodologies and caveats clearly to clients and internal stakeholders
Use AI and coding assistants effectively while taking full responsibility for reviewing and validating their output
Contribute to the development of analytical and data products as the team evolves

Skills & Experience:

1-3 years' Data Science experience, or equivalent demonstrated experience through graduate work, projects or competitions
Strong Python skills, particularly pandas and NumPy
Strong SQL skills, including CTEs, window functions and aggregation
A solid understanding of applied statistics, including hypothesis testing and confidence intervals
MMM (Marketing Mix Modelling) experience, or have worked in this environment
An understanding of selection bias, confounding and the assumptions behind statistical methods
Some knowledge of causal inference techniques such as A/B testing, difference-in-differences or matching
A habit of validating results against the underlying data rather than simply trusting that code has executed successfully
Strong written and verbal communication skills, with the ability to explain technical concepts clearly
A curious and sceptical mindset, with the instinct to investigate results that don't look right
Experience using AI or coding assistants, alongside the judgement to verify their output before using it