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Data Scientist
Job in
Greater London, London, Greater London, W1B, England, UK
Listed on 2026-02-15
Listing for:
Spectrum IT Recruitment
Full Time
position Listed on 2026-02-15
Job specializations:
-
IT/Tech
Machine Learning/ ML Engineer, Data Analyst
Job Description & How to Apply Below
Our client is looking for an experienced Data Scientist to design, build, and optimise machine learning models and advanced analytics solutions that support institutional priorities across a large, complex network. The role blends hands-on data science with strategic impact, using AWS technologies to deliver predictive insights that drive proactive interventions and data-driven decision-making. This is a hybrid role with the expectation of working 2 days pw in the London office.
Skillsand experience required
- Bachelor's degree in data science, Statistics, Computer Science, Mathematics, or similar
- Experience delivering predictive analytics or machine learning solutions
- Strong skills in Python, SQL, and ML libraries (e.g. scikit-learn, XGBoost, PyTorch, Tensor Flow)
- Hands-on experience with AWS ML services (Sage Maker, Lambda, Redshift)
- Ability to clearly communicate insights to non-technical stakeholders
- Strong analytical thinking, collaboration skills, and a results-driven mindset
- Build, tune, and maintain predictive and ML models using AWS Sage Maker
- Analyse large datasets and perform feature engineering to improve model performance
- Run experiments, test hypotheses, and optimise models for accuracy and value
- Monitor model performance and manage retraining over time
- Collaborate with Data Engineers, BI Developers, and Analysts to integrate outputs into dashboards and reports
- Partner with academic, operational, and IT stakeholders to translate insights into action
- Document models and support knowledge sharing and scalability
- Contribute to the expansion of predictive analytics into advanced ML/AI use cases
Spectrum IT Recruitment (South) Limited is acting as an Employment Agency in relation to this vacancy.
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