AI / Data Analyst

AI / Data Analyst

Salary: Up to £60,000

Location: London (Hybrid)

Travel: Occasional international travel (UK, Europe, US)

About the Role

Our client is a global technology group operating at the intersection of engineering, science, and digital innovation. They are investing heavily in AI, data, and connected technologies to transform both their products and operations.

This is a hands-on, early-career role designed for a technically curious graduate who wants to build real-world experience in data science, AI, and digital product development. You will sit within a central digital team supporting multiple business units on AI and data-driven initiatives.

This is not a finance-driven analytics role. The focus is on scientific, engineering, and operational data, including time-series and image data, with exposure to machine learning experimentation and modern AI tooling, including GenAI.

What You’ll Be Doing

Data Preparation and Engineering

• Collect, clean, and validate data from sensors, internal systems, APIs, and files.
• Build structured, reproducible datasets for analysis and modelling.
• Identify and resolve data quality and integrity issues.

Exploratory Analysis and Insight Generation

• Perform exploratory data analysis to identify trends, anomalies, and patterns.
• Translate findings into clear, structured insights for stakeholders.

Machine Learning and AI Support

• Support development and testing of machine learning pipelines.
• Work with time-series, tabular, and image datasets.
• Assist with experimentation, model comparison, and evaluation.
• Contribute to early-stage work in areas such as generative AI and language models.

Data Visualisation and Communication

• Build dashboards, charts, and reports using Python or BI tools.
• Present outputs clearly to technical and non-technical audiences.

Technology Research and Evaluation

• Assess AI tools and platforms, documenting strengths, limitations, and risks.
• Support evaluation of both internal and third-party solutions.

Governance and Best Practice

• Maintain clear documentation and reproducible workflows.
• Support responsible AI practices and data governance standards.

Ideal Background

Essential

• Degree in a scientific or technical discipline such as Physics, Chemistry, Biology, Engineering, Mathematics, or Data Science.
• If from a Computer Science background, proven exposure to scientific or experimental data.
• Working knowledge of Python (pandas, NumPy).
• Understanding of core machine learning concepts.
• Strong analytical thinking and attention to detail.
• Ability to communicate findings clearly.

Highly Desirable

• Experience with time-series or image data (academic or project-based).
• Exposure to machine learning workflows or experimentation.
• Experience with data visualisation tools.
• Familiarity with Git.
• Interest in generative AI and emerging AI technologies.

What They’re Looking For

• A graduate or early-career candidate within 0–2 years.
• Strong scientific or engineering mindset, not finance-focused.
• Highly organised with strong documentation habits.
• Logical thinker who uses AI tools appropriately, not blindly.
• Curious, proactive, and comfortable learning through experimentation.

Environment and Culture

• Work across a wide range of AI, IoT, and digital product initiatives.
• Exposure to modern AI tooling and real-world applications.
• International project exposure across Europe and the US.
• Strong team culture with regular social events and collaboration.

Working Pattern

• Hybrid model combining London office, remote work, and travel.
• Project-based international travel required.

Who This Role Suits

Someone early in their career who wants to apply data and AI in real-world scientific and engineering contexts, rather than sitting in a purely reporting or finance-driven analytics role.