Morgan McKinley
Business and Marketing Data Scientist

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Business and Marketing Data Scientist
Contract duration: Contract until 04/12/2026
Location: London, UK (3 days onsite, 2 days WFH)
Responsibilities:
- Strong understanding of statistical concepts and data analysis techniques, with the ability to extract insights from large datasets.
- Familiarity with creating data dashboards is required.
Experience:
- A minimum of five years of experience is required, with a preference for proficiency in Python.
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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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.
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As a Business & Marketing Data Scientist, you are a subject matter specialist for translating business problems from your supported organization or functional area into analytical solutions and insights. You provide technical mentorship in delivering project work including implementing data science solutions, improving data pipelines, developing evaluation metrics, or building statistical models that provide insights to the business. You create and implement reused and scaled solutions within the team's development process. You collaborate with supported teams and win stakeholder trust by translating business needs into tractable analyses or evaluation metrics. You work closely with product and engineering teams to analyze impact on product or our metrics (including daily activities, retention, churn).
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