Machine Learning Engineer

Duration: 5 weeks (with potential for extension)

Location: Remote (UK-based)

Start Date: ASAP

We are seeking an experienced Data & ML Contractor to deliver a proof of concept using static, structured datasets. This is a focused, pragmatic engagement centred on data preparation, feature engineering, and anomaly detection - with an emphasis on clear, interpretable outputs for stakeholders.

This is not a heavy Data Engineering or MLOps engagement. There is no requirement for live pipelines, streaming ingestion, or ongoing automated refresh. The successful candidate will work hands‑on to profile data, engineer meaningful features, develop detection logic, and communicate findings effectively to non‑technical stakeholders.

• Strong Python for data processing and analytics (e.g., pandas, numpy; scikit-learn or equivalent)
• Structured data expertise: joins, aggregations, data cleaning, handling missing data/outliers, basic data modelling concepts
• Feature engineering: ability to craft interpretable, business-relevant features
• Anomaly detection experience: practical knowledge of rule-based and statistical methods; ML-based approaches where appropriate
• Requirements & communication: ability to work with stakeholders, define success criteria, and explain outputs clearly

• Power BI / BI visualisation (or similar) to support validation and stakeholder-facing outputs
• Familiarity with Azure for accessing datasets or sharing PoC artefacts (basic storage/compute)
• Ability to outline what would be needed to scale the PoC toward production later (without implementing full MLOps now)

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