Data Scientist (Machine Learning)

Data Scientist (Machine Learning) – Initial 12 mth FTC £50,000+Bonus+Benefits-Remote working

My client are a leading Consultancy in the Commercial Sales arena helping Businesses and Retailers all across the UK.

Due to exciting growth we are building a new machine Learning team. With most of the team in place we are looking for aData Scientist (Machine Learning) to support the build and launch of our new Microsoft Fabric Lakehouse and machine learning platform. This is a largely remote role with on average just 1 day a month required in the office.

TheData Scientist (Machine Learning) willapply statistical and machine learning techniques to real commercial datasets, producing outputs such as impact analysis, ROI modelling, forecasting, and anomaly detection. The emphasis is on practical model delivery, documentation, and handover, rather than long-term operational ownership.

As our newData Scientist (Machine Learning) you will be responsible for:

• Build predictive, forecasting and anomaly-detection models
• Perform feature engineering & validation using Python / PySpark
• Work in Fabric Notebooks, Delta Lakehouse, and AutoML
• Embed models into production pipelines with our Data Engineering team
• Document and hand over deliverables

If you are an experienced Junior or Mid-levelData Scientist (Machine Learning) this could be a great opportunity for you. You should have experience of:

• Experience as a Data Scientist or advanced Data Analyst
• Strong analytical/statistical skills
• Practical Python modelling experience
• Good SQL for data exploration
• Clear communication of results to non-technical teams

Initially this is a 12 month Fixed Term Contract but with the work we have there is every chance of it becoming permanent. It would be an ideal role for a strong Junior/early Mid-level Data Scientist looking to take on more ownership and deliver real Production outcomes. This role is largely remote with just 1 day a month needed on average in the office. Interested? Apply now for an immediate interview.

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