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AI Deployment Specialist

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AI Deployment Specialist
My client, a financial services organisation is on the look for an AI Deployment Specialist to own the front end and back end of AI adoption across a live business area. You will identify and size AI use cases with business leadership, prioritise and sequence them, then lead the change management and adoption work needed to get them embedded and delivering measurable value.
You will work alongside a technical build team rather than being part of it. The role is not hands-on engineering: you need to be technical enough to define requirements, run evaluation and regression checks in a low-code or no-code way, interpret results and challenge the technical approach, without writing code or raising pull requests yourself.
A live example of the type of use case in scope: automating a client onboarding process that currently takes circa twenty four months to complete manually, involving document handling, data extraction, policy validation and compliance checks.
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.
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.
What you will do
- Work with business leadership to identify, size and build the case for high-impact AI use cases
- Prioritise and sequence use cases, balancing value, feasibility and organisational readiness
- Own adoption end to end, stakeholder engagement, training and change programmes so AI tools become embedded, not shelfware
- Track outcomes against the original business case and ensure deployments translate into measurable impact
- Act as the bridge between business stakeholders and the technical build team, defining requirements and running eval/regression pipelines
- Codify what works into a repeatable playbook the wider team can reuse
What you will bring
- 4 to 7 years' total experience, including time at a top-tier consulting firm or AI vendor
- A track record leading end-to-end AI or data science engagements, scoping, sizing value and owning delivery through to adoption
- Enough hands-on data science / ML grounding to scope problems credibly, judge feasibility and challenge a technical team, without needing to build full time
- Strong change management and stakeholder skills, able to drive adoption across leadership and operational teams
- Commercial fluency, comfortable framing AI work in terms of business value, ROI and operational impact
- Confidence working with senior stakeholders, including in a governance-heavy environment
- Comfort operating in a lean team, going deep on content rather than just running process


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Desirable
- Experience across varied industries rather than a single sector
- Private equity or portfolio value creation experience
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