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Data and AI Value Creation and Strategy, Leading Mid-Market Private Equity Fund, London, UK

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About our client
Our client is a leading mid-market private equity firm seeking to appoint an AI & Data professional to join its Value Creation team. Working directly with portfolio company leadership teams, you will identify, design, and deliver high-impact data and AI initiatives that drive commercial value. This is a broad, hands-on role spanning both strategy and execution, requiring the ability to engage confidently with C-suite stakeholders on business priorities while also providing informed input on data architecture, analytics platforms, and technical delivery. Across the portfolio, you will help businesses define pragmatic data strategies, develop modern data and analytics platforms, prioritise high-impact analytics and AI use cases, and build scalable capabilities that support long-term growth and operational improvement.
The successful candidate will have recent, hands-on experience leading the implementation of data and AI solutions, rather than solely providing advisory support.
What the job involves
- Partner with portfolio company leadership teams to identify data, analytics, and AI opportunities that deliver measurable commercial value
- Develop KPI frameworks, enhance reporting and forecasting capabilities, and help management teams prioritise initiatives based on business impact, feasibility, and speed to value
- Assess the maturity of portfolio companies' data and analytics capabilities and develop pragmatic 1–3-year transformation roadmaps
- Define scalable target-state data architectures and advise on governance, operating models, technology selection, and capability development, balancing long-term ambition with the practical realities of mid-sized businesses
- Lead or support the design and implementation of modern data and analytics platforms
- Provide technical guidance on data architecture, modelling, engineering, and analytics enablement while working effectively across both internal and third-party delivery teams
- Maintain a hands-on approach where required, contributing directly to solution design and delivery
- Identify and evaluate high-value AI and Generative AI use cases across the portfolio, distinguishing practical commercial opportunities from emerging market trends
- Integrate AI capabilities into broader data and analytics strategies to accelerate growth, improve decision-making, and drive operational efficiencies
- Build trusted relationships with portfolio company executives, investment professionals, and value creation teams
- Communicate complex technical concepts clearly to both technical and non-technical stakeholders
- Manage multiple concurrent engagements across a diverse portfolio, balancing competing priorities while maintaining a high standard of delivery
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.
Who we are looking for


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- Degree educated in a technical or quantitative discipline such as Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related field
- Demonstrable experience in data and analytics consulting, modern data platform implementation, analytics transformation, or technology strategy
- A proven track record of delivering data and AI initiatives from strategy through to implementation, with recent hands-on delivery experience rather than purely advisory responsibilities
- Experience working with mid-sized organisations, private equity-backed businesses, or high-growth environments is advantageous
- Comfortable operating in fast-paced environments, managing multiple stakeholders, and balancing strategic thinking with practical execution
- Cloud Platforms: Experience with one or more cloud environments, such as Microsoft Azure, Amazon Web Services (AWS), or Google Cloud Platform (GCP)
- Data Engineering & Transformation: Building and delivering modern data platforms, data warehousing, ETL/ELT pipelines, orchestration, and analytics engineering
- Business Intelligence & Visualisation: Developing dashboards and reporting solutions using tools such as Power BI, Tableau, or Looker
- Programming: Proficiency in SQL and at least one programming language such as Python, R, or Scala
- Data Governance & Quality: Experience implementing data governance frameworks, data quality controls, metadata management, and master data practices
- AI & Generative AI: Practical experience identifying, developing, or deploying AI and Generative AI use cases within commercial environments, including familiarity with modern LLMs and AI-enabled analytics solutions
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