Data Scientist, Customer Marketing

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Data Scientist, Customer Marketing, London

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Client:

Blue Pelican
Location:

London, United Kingdom
Job Category:

Other
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EU work permit required:

Yes
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Job Reference:

269032c5a856
Job Views:

5
Posted:

29.06.2025
Expiry Date:

13.08.2025
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Job Description:

Data Scientist, Customer Marketing (CRM Analytics)
Location:

Hybrid working, Central London offices, 10 days in every month.
Salary:

£50,000 - £55,000 plus 10% bonus, pension, healthcare, life assurance, etc.
You’ll be joining an 800 person B2C fintech which happens to have one of the largest consumer databases in the UK, made up of over of 30m customers.
The team you’ll be joining is their CRM division, and the projects you’ll be working on all align to customer marketing initiatives. Looking at creative use and application of data in a marketing context.
Making recommendations on how to improve targeting by looking at past performance of campaigns. Or working on the application and deployment of data science solutions such as ML and next best action models, and how they could be incorporated and activated into marketing activities to deliver value for the company’s customer marketing activity.
Or looking at new data assets either already within the business, or via third party partnerships which could provide potential value when activated in the right way within CRM campaigns. Either to drive personalisation, identify new potential trigger points and moments of truth within the customer lifecycle, which could lead to new customer journeys, or could be utilised to enrich targeting strategies for existing campaigns to help elevate their performance.
Plus have the technical capabilities to be able to sit down with data engineers to explain what’s needed when it comes to certain data assets and tables, so you’re able to help shape how data feeds operate and ensure they’re as useful as possible in how they’re delivered, and help activate that data asset so it can be utilised by the CRM team in their marketing campaigns.
You will be the subject matter expert on customer and campaign data, in charge of making sure the right data is available to the CRM to enable them to deliver a best in class customer marketing programme. Successfully working across data strategy, CRM analysis and predictive modelling, giving you a role which will cover multiple disciplines including data planning, CRM analytics, decision science and data science.
From a technical perspective, all that’s needed is a solid stats background with a good handle on SQL as well as Python coding skills. With experience analysing large relational databases.
Alongside this, also have a natural curiosity and interest to want to look into the ‘why’ and what’s going on with customer behaviour and CRM campaigns.
What makes this opportunity so interesting?
It’s got to the people, environment and the employer brand itself.
To many, this employer is a destination one. Prolific and incredibly high profile. Their consumer champion status makes them a place people tend to want to become a part of because their ambition is to do good by the consumer. In doing so they also achieve good things for themselves in the process.
If you want to work in a place made up of impressive people and inspirational leaders, this is the place to be. The environment is one recognised for pace and ambition, yet remains kind and caring.
Experience Needed
A CRM or marketing related analytics background is essential – so you understand things like segmentations and how to do them. Logistic regression and predictive analytics, good knowledge of data science techniques within a marketing/commercial environment (not product related) will be beneficial
Solid analytics skills, with the story telling/insight skill – not just reporting. This is not a BI/Reporting role. So you know how to identify trends in data, generate meaningful insights and translate them into recommendations for marketing use
Got to have hands-on SQL and Python skills and have experience of working with Cloud warehouses like Redshift
Natural curiosity around the mechanics behind the ‘why’ in data findings and analytics outputs
Comfortable in pacey environments like you’d expect in retail, digital or tech

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