Business & Marketing Data Scientist – Marketing Analytics

Business & Marketing Data Scientist – Marketing Analytics

Client: GLOBAL ICONIC TECH BRAND

Location: Central London

Pay rate: £54.81 per hour PAYE

Contract: ASAP until 4 December 2026

Working pattern: Hybrid – Tuesday to Thursday in the office, Monday and Friday remote

Hours: 40 hours per week

The Role

We are looking for an experienced marketing analytics professional to join its EMEA Marketing team, supporting products including AI products and subscription-based services.

Despite the formal title, this is not a traditional data science or machine-learning role. The position is focused on digital marketing analytics, audience intelligence, campaign targeting, experimentation, dashboard creation and turning large volumes of data into clear commercial recommendations.

You will be the only dedicated analyst within a team of approximately seven people, so you must be comfortable working independently, taking ownership of analysis and confidently advising senior marketing stakeholders.

Key Responsibilities

• Create audience intelligence to identify which customer groups are most likely to benefit from specific products.
• Analyse why particular audiences may be interested in a product and use those insights to shape campaign strategy.
• Work with very large and complex datasets to identify meaningful audience, campaign and product trends.
• Use aggregate customer and marketing data to inform targeting, segmentation and channel strategy.
• Analyse digital marketing performance across Google Ads, SEO, YouTube, social media and other digital channels.
• Build and maintain dashboards, reports and spreadsheet-based analysis.
• Design, analyse and interpret A/B tests and digital marketing experiments.

Essential Skills and Experience

• At least five years of experience in marketing analytics, digital marketing analytics, audience insights or a related field.
• Strong experience analysing digital advertising and campaign performance.
• Good understanding of Google Ads, SEO, YouTube marketing and social media channels.
• Experience creating audience segments and targeting strategies.
• Proven experience working with very large and complex datasets.
• Strong dashboard creation and reporting experience.
• Advanced spreadsheet skills.
• Practical experience using SQL or Python for data extraction, manipulation, validation and analysis.
• Candidates do not need to be advanced in both SQL and Python but must be confident using at least one.
• Experience designing and evaluating A/B tests or marketing experiments.
• Strong understanding of statistics, averages, trends, performance metrics and experimental results.
• Ability to turn analysis into clear commercial and marketing recommendations.

Relevant Candidate Backgrounds

The hiring manager is open to candidates from:

• Advertising and media agencies
• Financial services organisations
• Start-ups and scale-ups
• Meta, Amazon or other major technology companies
• Contract roles within technology or digital businesses

Relevant job titles may include:

• Senior Marketing Analyst
• Digital Marketing Analyst
• Audience Insights Analyst
• Marketing Intelligence Analyst
• Campaign Analytics Manager
• Performance Marketing Analyst

Interview Process

The interview will focus heavily on examples of previous work, particularly dashboards, experimentation and marketing analysis.

Candidates should be prepared to discuss:

• The business or marketing problem they were solving
• The dashboard, report or analytical solution they created
• The size and complexity of the datasets involved
• The tools and data sources used
• How they selected the relevant metrics
• Any A/B testing or experimentation they conducted
• The insights they identified
• The recommendations they made
• The impact their work had on targeting, campaign performance or business decisions

Candidates focused primarily on machine learning, advanced predictive modelling or highly technical data science are unlikely to be the right fit. The strongest profile will combine digital marketing knowledge, practical analytics, large-scale data experience, dashboard creation, experimentation and the confidence to recommend clear actions.