Kinarden Search
Data Scientist

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An exciting opportunity has arisen within a global consultancy's new and growing Data Science and AI team working on a range of machine learning, analytics and model validation projects. This role will suit individuals with experience in data science, machine learning or applied AI who are looking to work across a variety of complex business and technology challenges.
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.
The opportunity: Developing and validating machine learning models Supporting the review and assessment of AI and data science solutions Working with large and complex datasets to generate meaningful insights Collaborating with technical and non-technical stakeholders Contributing to the development of innovative AI and analytics capabilities


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Key requirements: Strong Python skills (essential) Experience developing and validating machine learning models Knowledge of machine learning frameworks and statistical modelling techniques Exposure to LLMs, Generative AI or Agentic AI Experience with cloud platforms such as Azure or AWS desirable Strong communication and stakeholder management skills
“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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