Staff Data Scientist - Paid Marketing
Job description
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Staff Data Scientist - Paid Marketing
London - x2 days a week
Up to £113,000 plus bonus and benefits
This is a fantastic opportunity to join a high-growth, product-led business where data drives every marketing decision. You will shape how performance is measured across a major digital brand, building new attribution and LTV capabilities that directly influence strategy.
The Company
They are a fast-scaling, community-focused digital marketplace with a strong app footprint and a mission-led culture. Their marketing team is expanding and investing heavily in data to improve performance across paid and brand channels. With an international user base and a modern tech stack, they offer the chance to innovate, experiment, and deliver impact at scale.
The Role
You will join the marketing analytics function, owning attribution modelling and the measurement framework that powers paid marketing decisions.
Key responsibilities include:
* Leading the development, maintenance, and optimisation of attribution models for sign-ups and paid activity.
* Building measurement capabilities, including CLV and LTV modelling for strategic forecasting.
* Delivering complex, in-depth analysis to explain performance and guide future investment.
* Partnering with stakeholders across paid, brand, and wider marketing teams.
* Driving the measurement roadmap and ensuring clarity on key metrics across the business.
* Providing BAU support while also setting long-term direction.
Your Skills and Experience
You will bring:
* Strong SQL skills.
* Excellent Python capability for developing analytics and attribution models.
* Proven experience in marketing analytics within an app-based or digital-first environment.
* Ability to communicate complex measurement concepts clearly to non-technical stakeholders.
* Experience owning attribution frameworks and performance measurement processes.
What They Offer
* Up to 113k plus benefits
How to Apply
If you are passionate about building best-in-class measurement for a fast-moving digital brand, apply today to find out more.
Key skills
AI-extracted from the job advert
Application advice
5 AI-generated recommendations to maximise your chances.
⭐ Highlight your Python and SQL expertise prominently as these are the core technical requirements for building attribution models
📊 Quantify your attribution modelling impact: "Built MMM reducing CAC by 23% across 8 paid channels"
🎯 Emphasise app-based or digital marketplace experience as they specifically value this background
🔍 Showcase LTV/CLV modelling projects with concrete business outcomes and forecasting accuracy
🤝 Demonstrate your ability to translate complex measurement concepts to non-technical marketing stakeholders
Suggested CV bullets
3 bullets our AI drafted for this specific advert, mirroring its ATS keywords.
Add these 3 bullets under your most recent experience:
- •Developed multi-touch attribution model using Python reducing paid marketing CAC by 28% across 12 channels for 2.3M monthly active users
- •Built CLV forecasting framework in SQL predicting 18-month customer value with 94% accuracy, informing £8.2M annual marketing budget allocation
- •Led attribution measurement roadmap for app-based marketplace, delivering stakeholder training to 15 marketing team members on new framework adoption
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Dear Hiring Manager,
Your Staff Data Scientist role at this fast-scaling digital marketplace perfectly aligns with my expertise in attribution modelling and marketing analytics. Having built LTV frameworks and attribution models using Python and SQL, I'm excited by the opportunity to shape measurement strategy for a community-focused platform with international reach.
My background in developing marketing attribution frameworks for app-based businesses has equipped me with the technical skills and stakeholder management experience needed to drive measurement roadmaps whilst delivering BAU support. I understand the complexities of translating measurement insights into actionable marketing strategy.
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Interview questions
10 questions generated from this advert.
Technical
- ›How would you design an attribution model for a multi-touch customer journey across paid and organic channels?
- ›Walk me through your approach to building a customer lifetime value model for an app-based business
- ›How do you handle data quality issues when building marketing attribution frameworks?
- ›Explain how you would measure incrementality in paid marketing campaigns
- ›What statistical methods would you use to validate the accuracy of your attribution models?
Behavioural
- ›Tell me about a time you had to explain complex attribution concepts to non-technical marketing stakeholders
- ›Describe a situation where your measurement framework directly influenced marketing strategy
- ›Give an example of how you've balanced BAU support with strategic measurement initiatives
- ›Tell me about a time you had to build stakeholder buy-in for a new measurement approach
- ›Describe how you've handled conflicting measurement requirements from different marketing teams
STAR answer examples
Model answers using the Situation-Task-Action-Result framework. Adapt to your own experience.
Tell me about a time you had to explain complex attribution concepts to non-technical marketing stakeholders
Describe a situation where your measurement framework directly influenced marketing strategy