Are you an enthusiastic early‑career data professional with a passion for AI, analytics, and solving real business problems?
An innovative and fast‑paced organisation in the metals trading sector is looking for a proactive AI & Data Analyst to join its Projects Team. This is a hands‑on role where you’ll help deliver data products and AI‑powered insights that directly shape business decisions. As an AI & Data Analyst, you’ll work across the full data lifecycle from sourcing and transforming data to exploratory analysis, feature development, modelling support and clear communication of results. You’ll collaborate closely with business users, contribute to good engineering practices, and play a key role in producing dashboards and analysis that make a tangible impact.
What You’ll Be Doing
- Integrating and transforming data from internal systems and external sources; maintaining essential documentation and metadata.
- Assessing datasets for quality, completeness and bias; proposing improvements and tracking their impact.
- Conducting exploratory analysis on structured and unstructured data and producing clear dashboards/visualisations (Power BI/Tableau).
- Supporting development and evaluation of lightweight machine‑learning models, ensuring reproducibility and version control (Git).
- Using AI‑assisted development tools to accelerate delivery while upholding accuracy, transparency and auditability.
- Working with stakeholders to refine requirements, translate business questions into data tasks, and support UAT for analytics releases.
- Contributing to best practices in security, privacy, responsible AI, coding standards, documentation and simple automation.
Who We’re Looking For
- A graduate in a quantitative field (Computer Science, Data/AI, Maths/Stats, Engineering) or equivalent experience.
- Strong foundations in Python (Pandas, NumPy, visualisation libraries; scikit‑learn; exposure to PyTorch useful), SQL, BI tools (Power BI/Tableau), and Git.
- Understanding of basic data modelling concepts and metadata management.
- Nice to have: exposure to modern data engineering tools (cloud data warehouses/lakehouses, ETL/ELT, orchestration tools, APIs, CI/CD).
- Solid grounding in statistics and model evaluation.
- Clear communicator able to present technical findings to non‑technical stakeholders.
- Curious, analytical, and comfortable working with ambiguity and iterative delivery.
- Commercial awareness; experience or interest in financial markets is a plus.
- Able to work effectively in a hybrid environment.
- Typically up to 3 years’ experience in data/analytics (internships and project work welcome).
Why Apply?
This is an exceptional opportunity for an early‑career analyst to gain hands‑on experience with real‑world data challenges, work with modern AI tools, and develop both technical and commercial skills in a dynamic environment.
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