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Data Scientist, Causal Inference
London - 1x every 6 weeks
The Company
They are a global, product led organisation operating at scale with a highly sophisticated data environment. The business places data at the centre of decision making and continues to invest heavily in advanced analytics and AI capabilities. Their datasets are rich and complex, enabling deep analysis of customer behaviour across the full lifecycle. This role sits within a dedicated CLV team focused on maximising long term customer value.
The Role
You will focus on applying causal inference techniques to quantify the true impact of customer behaviours, product features and commercial initiatives. Your work will directly influence how the business invests in growth, retention and engagement. Responsibilities include:
- Applying causal inference methodologies to measure incrementality and customer lifetime value drivers
- Designing and analysing experiments, quasi experiments and observational studies
- Developing frameworks to distinguish correlation from causation in customer behaviour
- Using techniques such as propensity score matching, double machine learning and counterfactual modelling
- Measuring the incremental impact of actions such as product usage or subscription adoption
- Working with large scale customer and product datasets to identify value drivers
- Collaborating with stakeholders to translate complex analysis into clear business recommendations
- Supporting the productionisation of analytical solutions
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Your Skills and Experience
- Strong statistical foundation with the ability to apply rigorous analytical methods
- Experience working with customer, product or subscription data
- Knowledge of causal inference techniques such as propensity scoring, incrementality testing and counterfactual analysis
- Experience designing experiments and interpreting A B testing results
- Ability to translate complex technical outputs into clear business insights
- Strong collaboration and stakeholder management skills
- Proactive approach with a focus on delivering commercial impact
- Academic background in a quantitative discipline such as mathematics, statistics, economics or similar


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What They Offer
- Competitive salary and comprehensive benefits package
- Clear progression opportunities within a growing data science function
- Exposure to cutting edge causal inference and experimentation methodologies
- Opportunity to work on large scale, high impact data problems
- Collaborative and forward thinking data environment
How to Apply
To find out more or apply for this Data Scientist, Causal Inference role, please get in touch.
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