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Data & AI Analyst [Contract]

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Data & AI Analyst [Contract], Investment Manager, London [Onsite]
We are working with a long-standing investment house that is seeking to hire a Data & AI Analyst, on a contractual basis [6-month rolling contract], to support the business through a period of significant data transformation. This is a role where you'll work across the business, promoting change and identifying use cases for emerging technologies. You will also support wider initiatives to improve business-wide automation practices.
Working closely with senior stakeholders, you will help evaluate how data, AI, and emerging technologies can be leveraged to drive more effective decision-making, streamline business processes, and support long-term strategic objectives. It is a broad role with significant autonomy and stakeholder exposure, working closely with teams across investment, operations, and technology.
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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.
Responsibilities:
- Support the delivery of data, AI, and automation initiatives across the business.
- Partner with stakeholders to identify opportunities for process improvement and technology adoption.
- Assess emerging technologies and translate technical concepts into practical business applications.
- Contribute to the implementation and embedding of new tools, processes, and AI-driven ways of working.
Requirements:
- 2+ years' experience in AI, machine learning, data science, analytics, quantitative research, or a related field. Exceptional candidates from alternative backgrounds will also be considered.
- Working knowledge of tools such as Python, SQL, and Power BI (or other BI tools) for data analysis, reporting, and automation.
- Excellent communication skills, capable of engaging effectively with both technical and non-technical stakeholders.
- Undergraduate degree from a leading university in a quantitative, mathematical, technical, or STEM-related discipline.


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