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# Data Scientist

- **Company:** Anson McCade
- **Location:** London, UK
- **Experience:** Expert
- **Salary:** £80,000.0 - £120,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Computer Vision, Microsoft Azure, Big Data, Data Cleansing, Python (Programming Language), Machine Learning, Tensorflow, Feature Engineering, Pytorch, Model Validation, Git, Scikit Learn, Machine Learning Operations
- **Published:** July 22, 2026
- **Apply:** https://www.totaljobs.com/job/data-scientist/anson-mccade-job107725459

## About the Role

* Strong Python programming skills with experience across data science and machine learning workflows.
 * Solid understanding of machine learning algorithms and statistical modelling.
 * Experience using ML libraries such as scikit-learn, TensorFlow, or PyTorch.
 * Strong knowledge of data preprocessing, feature engineering, and model evaluation.
 * Experience working with large datasets and applying analytical techniques.
 * Familiarity with Git and reproducible research practices.

Desirable Experience

 * Exposure to cloud platforms such as AWS, Azure, or GCP.
 * Knowledge of MLOps practices and tooling.
 * Experience in areas such as NLP, time series analysis, or computer vision.
 * Comfortable presenting technical work and insights to stakeholders.

## Description

Are you a Data Scientist looking to work on challenging AI projects that deliver real-world impact?, You'll work alongside data scientists, engineers, and domain experts to design, build, and deploy data-driven solutions. This is an opportunity to work on varied and impactful projects while continuing to develop your technical expertise in AI and machine learning., * Apply statistical and machine learning techniques to solve complex business and operational challenges.

 * Perform data cleaning, transformation, and feature engineering across large and diverse datasets.
 * Build, train, validate, and optimise machine learning models.
 * Translate technical findings into clear insights for both technical and non-technical stakeholders.
 * Collaborate with engineering teams to deploy models into real-world environments.
 * Keep up to date with developments across AI, machine learning, and data science.


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