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Sanderson

Machine Learning Engineer

London
£700 – £750/day
Posted about 12 hours ago
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Machine Learning Engineer

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.

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Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your 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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It 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.

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Strong

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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Strong

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.

£700-750/day overall assignment rate to umbrella

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Fully remote

6 month initial


A FTSE 100 retail client are on the look for multiple Machine Learning Engineers to join their data science function to drive cutting-edge ML technology across the business.

We’re looking for individuals with:

  • Experience: Proven background as a Machine Learning Engineer
  • Technical Skills:
    • Strong in SQL and Python (Pandas, Scikit-learn, Jupyter, Matplotlib)
  • Data transformation & manipulation:
    • Experience with Airflow, DBT and Kubeflow
  • Cloud:
    • Experience with GCP and Vertex AI (developing ML services)
  • Deep learning and Natural Language Processing (NLP):
    • LLM (Large Language Model)
  • Expertise:
    • Solid understanding of computer science fundamentals and time-series forecasting
  • Machine Learning:
    • Strong grasp of ML and deep learning algorithms (e.g. Logistic Regression, Random Forest, XGBoost, BERT, LSTM, NLP, Transfer Learning)
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Skills

SQL
Python
Pandas
Scikit-learn
Jupyter
Matplotlib
Airflow
DBT
Kubeflow
GCP
Vertex AI
LLM
Time-series forecasting
Deep Learning
NLP
Transfer Learning

Location

London, England, United Kingdom

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