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Renishaw

Principal Data Scientist I

London
Posted 14 days ago
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Principal Data Scientist – Propulsion Labs at Cirium

About the Business

At Cirium, our goal is to keep the world connected. We are the industry leader in aviation analytics, helping our customers understand the past, present, and predict what will happen tomorrow. Our mission is to transform the aviation industry by enabling airlines, airports, travel companies, tech giants, aircraft manufacturers, financial institutions, and many more to accelerate their digital transformation.

About Our Team

Propulsion Labs is Cirium’s innovation group, focused on solving complex, high-impact problems in aviation analytics. We work in small, collaborative teams to explore ideas, test solutions, and scale products that deliver meaningful value to customers. Our environment supports autonomy, learning, and inclusive collaboration.


About the Role

As a Principal Data Scientist, you will be a senior individual contributor who brings deep technical expertise while shaping best practices across the data science community.

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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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.

You will work closely with partners across product, engineering, and the business to design and deliver data-driven solutions. This role combines technical leadership, collaboration, and hands-on development to tackle complex, real-world problems in aviation analytics.

Responsibilities

  • Act as a technical authority for advanced analytics, machine learning, and generative AI, defining and evolving best practices for scalable and robust solutions
  • Provide thought leadership on emerging technologies and methodologies relevant to aviation analytics
  • Mentor and coach data scientists, supporting continuous learning and technical excellence
  • Collaborate with product managers, engineers, and domain experts to align data science initiatives with business goals
  • Translate complex technical insights into clear, actionable recommendations for stakeholders
  • Lead by example through hands-on coding, modelling, and solution design
  • Design, prototype, and validate innovative approaches to high-impact problems
  • Partner with engineering teams to deploy models into production environments

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Requirements

  • Strong experience working with large, complex, real-world datasets, ideally in aviation or related industries
  • Expertise in data wrangling, feature engineering, and building scalable data pipelines
  • Deep expertise in at least one advanced analytics area, with experience across several of the following:
    • Predictive modelling on tabular data
    • Deep learning
    • NLP and large language models
    • Generative AI pipelines
    • Simulations
    • Graph-based models
    • Time-series forecasting
    • Geospatial modelling
    • Causal inference
    • Reinforcement learning
    • Optimisation
    • Anomaly detection
  • Proven experience deploying, or partnering to deploy, customer-facing machine learning systems into production
  • Ability to collaborate across disciplines and communicate technical concepts to non-technical audiences
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Skills

Machine Learning
Generative AI
Predictive Modelling
Natural Language Processing
Data Wrangling
Feature Engineering
Data Pipelines
Time-Series Forecasting
Geospatial Modelling
Causal Inference
Reinforcement Learning
Optimization
Anomaly Detection
Deep Learning
Graph-Based Models
Technical Leadership

Location

London, England, United Kingdom

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