Eames Consulting
Finance Data Specialist

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A specialist Insurer based in London (City) are looking for a Finance Data Specialist to join the Digital Finance function.
Role
A finance data scientist role blending data science with the finance and actuarial function of a specialty insurance business. The person in this role would apply data science techniques to financial and actuarial data, build predictive and analytical models, and design automated workflows (leaning heavily on Databricks) to cut down on manual, Excel-based processes and improve forecasting, reporting and decision-making.
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.
Day to day, you will:
- Pull together large financial and actuarial data sets
- Build models to flag risk factors and data quality issues
- Create Power BI dashboards that make the insights usable for stakeholders
- Work closely with finance, actuarial and IT teams to spot automation opportunities
- Keep data secure and well-governed
- Document sources and processes for audit purposes


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Skills
On the skills side, you need:
- A technical background in finance, actuarial science, or data analytics
- Hands-on experience with Power BI, SQL, R, and Databricks
- A solid grasp of financial or actuarial processes
- Strong communication skills to translate complex analysis for both technical and business audiences
General insurance experience, data governance exposure, and a qualified accountancy or part-qualified actuarial qualification is essential.
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Jessica, London
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