Montash
Data Architect

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Data Architect - AI/ML Matching
Initial Contract Length: 6 months (contract-to-perm considered)
Work Location: Hybrid - Flexible
IR35 Status: Inside IR35
Industry: Public Services
Interview Process: One Stage
Security Clearance: Active SC Clearance required, with willingness to undertake NPPV3
Start: ASAP, following clearance transfer
AI/ML Matching, Entity Resolution and AWS Data Tooling Expertise mandatory
We are working alongside a leading consultancy provider to deliver a critical programme for a major public sector client, seeking a Data Architect with strong expertise in Entity Resolution and AI/ML-driven matching, to design and implement scalable, secure, high-quality data architectures enabling accurate matching, deduplication and linkage of complex datasets to support decision-making and analytics.
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.
Key Responsibilities:
- Lead the design and implementation of AI/ML-powered entity resolution (matching) solutions across multiple complex data sources
- Develop and optimise record linkage, deduplication, clustering and matching algorithms, incorporating machine learning models to improve match accuracy beyond rules-based approaches
- Define and manage golden record/master data models and entity hierarchies
- Establish rules and ML-supported logic for standardisation, matching, survivorship and merging of records
- Monitor and continuously improve entity resolution performance, including accuracy, precision/recall and scalability of matching models
- Champion and embed AI/ML-based matching approaches as the core methodology, moving beyond traditional deterministic matching where appropriate
- Leverage AWS data tooling to build, deploy and scale matching pipelines and ML-supported data architectures


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What We're Looking For:
- Active SC Clearance, with willingness to undertake NPPV3
- Proven, hands-on expertise in AI/ML-based entity resolution and matching this is a mandatory requirement, not a nice-to-have
- Strong background in Master Data Management (MDM) and entity resolution, including record linkage, deduplication and clustering techniques
- Experience defining golden record/master data models and survivorship rules
- Strong AWS data tooling expertise and experience
- Track record improving matching algorithm performance (precision, recall, scalability) using AI/ML techniques
Security Clearance: Active SC Clearance is required for this role, with a willingness to undertake NPPV3. Candidates must hold current SC. Non-SC candidates will not be considered.
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