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Senior Data Science Manager

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Senior Manager, Data Science (AI / Machine Learning)
Industry
Information & Analytics / AI for Research & Science
Work setting
Hybrid (London-based, flexible working)
Role summary
Define and lead AI / data science strategy across ML, NLP, search, and generative AI
- Lead end-to-end development of production AI systems (experimentation → deployment)
- Oversee development of LLM, RAG, search, recommendation, and NLP-based systems
- Establish frameworks for model evaluation, performance, and responsible AI
- Translate business and product goals into data science roadmaps and solutions
- Partner with product, engineering, and business leaders to drive strategy
- Lead, coach, and grow high-performing data science teams
- Ensure scalable, production-ready ML systems across large datasets
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.
Start with a chat, not a search bar
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.
See breakdownIt searches the market for you
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.
Requirements
- Strong background in data science / ML / AI (incl. NLP, deep learning, experimentation)
- Experience building and deploying production AI/ML systems at scale
- Proven leadership of technical teams in complex product environments
- Strong experience with large datasets and applied statistical modelling
- Experience with modern AI systems (e.g. LLMs, embeddings, RAG, search systems)
- Strong stakeholder management and ability to translate ambiguity into strategy


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Work style
- Hybrid working model with flexible hours
- Cross-functional global teams (product, engineering, research)
- High-impact AI environment focused on science and research innovation
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
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