Day1data
Data Analyst - Marketing

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Data Analyst - Marketing
Location: London (Hybrid - Chancery Lane Office)
Employment type: full time
Seniority: mid/senior
About Day1Data
Day1Data is a fast-growing B2B data analytics startup helping marketing and finance teams measure incrementality & make smarter marketing decisions. From marketing mix modelling to forecasting and data infrastructure, we help companies know what drives true growth. We work with leading global brands and are scaling rapidly - this is a great time to join a small, high-impact team.
Role overview
We are seeking a Marketing Scientist to join our team. This role will focus on experimentation, econometric modelling and the creation of actionable marketing insights. You will play a pivotal role in analysing customer acquisition and retention performance, designing measurement frameworks and building predictive models that influence commercial and strategic decisions.
Experimentation & Causal Inference
- Design, execute, and analyse experiments including geo-testing, A/B and multivariate testing.
- Use causal inference methods (e.g. synthetic control, difference-in-differences) to measure the incremental impact of marketing initiatives.
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.
Marketing Mix Modelling (MMM) & Econometrics
- Develop and maintain econometric models to evaluate marketing effectiveness and optimise investment allocation.
- Leverage multiple modelling techniques: Bayesian / Frequentist
- Contribute to long-term planning through investment forecasting and budget optimisation.
Acquisition & Retention Analytics
- Analyse performance across acquisition channels and customer cohorts, identifying key drivers of customer behaviour and retention.
- Track and optimise KPIs such as CAC, LTV, churn, and conversion across the lifecycle.
Predictive Modelling & Segmentation
- Build and deploy models for churn prediction, CLTV forecasting, and customer segmentation.
- Use model outputs to inform lookalike targeting, personalisation strategies, and performance marketing.
Attribution & Measurement
- Develop multi-touch attribution models to assess marketing effectiveness across channels.
- Model expected outcomes of marketing initiatives and quantify their commercial impact.
Stakeholder Collaboration
- Partner with marketing, finance, data science, and product teams to align on business objectives and translate analytical insights into action.
- Present findings in a clear, compelling way to both technical and non-technical stakeholders.


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What you’ll need
- Proven experience (2–4 years) in an analytics or data science role.
- Strong command of experimentation design and analysis (especially geo-based and incrementality testing).
- Experience in building MMM or econometric models.
- Proficiency in SQL and Python.
- Experience with attribution modelling and measurement frameworks.
- Familiarity with causal inference techniques (e.g., Bayesian structural time series, CausalImpact, etc.).
- Exposure to cloud-based analytics environments (e.g., BigQuery, Snowflake).
What we offer
- Competitive salary
- Equity
- Bonus
- Growth opportunities - A chance to build your career at a fast-paced data business, working on AI projects
- Ownership and autonomy - Real ownership and an opportunity to make a significant impact on our journey
- Collaborative culture - A fast-paced, energetic environment where big ideas are encouraged
Website: https://day1data.co.uk/
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