TAGMATIX360
Senior Data Analyst

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Job Summary
The Senior Data Analyst supports the organisation's objective of enhancing supervisory effectiveness through better use of entity and regulatory data. The role helps transform how Supervision teams identify risks, prioritise interventions and monitor firms, delivered through data-driven insights, dashboards, analytical tools and supervisory intelligence. It sits within a live testing programme for a regulatory data reporting regime. The analyst contributes to systems acceptance, firm feasibility and supervisory usability of the data being collected. The outcome is greater confidence in the regulatory data build through faster, more thorough testing.
Essential Skills
- SQL and large-scale data analysis across complex, multi-source datasets
- AWS services such as S3, DynamoDB, Athena, etc
- Data visualisation and dashboarding in Tableau or Power BI
- Data quality assessment, validation and improvement
- Stakeholder management across business and technical audiences
- Regulatory or financial services experience
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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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.
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No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Desirable Skills


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- Familiarity with regulatory or financial data reporting regimes
Key Responsibilities
- Supporting Supervisory Outcomes: Analyse risk indicators, alerts and supervisory insights to enable risk-based supervision and decision making.
- Regulatory Data Analysis: Analyse authorisation, holdings, transactions, legal entity and regulatory reporting data. Create integrated views across firms and entities so supervisors see a coherent picture rather than fragmented sources.
- Supervisory Intelligence and Risk Analytics: Identify trends, anomalies, concentrations and emerging risks. Support thematic reviews, quantitative investigations and synthesis of alerts.
- Data Quality and Improvement: Assess data quality, implement validation controls and validate legal entity identifiers (LEIs). Enrich core datasets using external sources such as GLEIF, Companies House and market data proxies.
- Reporting and Decision Support: Develop Tableau dashboards, management information and self-service analytics for Supervision teams, moving towards reusable, automated reporting.
- Business Analysis and Stakeholder Engagement: Gather requirements, facilitate workshops and translate supervisory challenges into analytical solutions. Cohere disparate and conflicting business needs into workable plans through engagement and governance forums.
- Future State Capability: Support the move towards automated reporting, advanced analytics, continuous monitoring and early-warning indicators, building a mature supervisory intelligence capability.
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