Data Scientist - Consumer Behaviour

Datatech Analytics; City Of London; Hybrid; GBP 45,000 - 60,000; Full time

Job summary

Datatech Analytics in Central London is seeking a Data Scientist to analyze consumer behaviour data and deliver insights across leading brands. You’ll apply rigorous statistical thinking to large-scale datasets and contribute to client reporting and data products.

The role involves defining cohorts, applying causal inference methods, and developing pipelines, with 1–3 years of experience and strong Python/SQL skills. Hybrid working with three days in office per week.

Qualifications

• 1–3 years of Data Science experience or equivalent (graduate projects/competitions).
• Strong Python skills, especially pandas and NumPy.
• Strong SQL skills including CTEs, window functions and aggregation.
• Solid understanding of applied statistics (hypothesis testing, confidence intervals).
• MMM experience or exposure to marketing mix modelling environment.
• Awareness of selection bias, confounding, and assumptions behind methods.
• Knowledge of causal inference techniques such as A/B testing, diff-in-diffs or matching.
• Strong written and verbal communication skills; ability to explain technical concepts clearly.
• Experience using AI or coding assistants with rigorous validation of outputs.

Responsibilities

• Work with large-scale behavioural datasets covering consumer activity across 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, diff-in-diffs and matching.
• Investigate selection bias, confounding and other factors affecting result validity.
• 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 anomalies.
• Write clear, maintainable Python code reusable by others.
• Collaborate 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 reviewing outputs.

Skills

Data Science

Python

SQL

Statistics

MMM

Causal Inference

Communication

Curiosity

Job description

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

Candidates must have the right to work in the UK without sponsorship requirements.