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# Assistant Manager, Data Science and Machine Learning, Audit and Assurance

- **Company:** Deloitte
- **Location:** London, UK
- **Contract:** Permanent contract
- **Skills:** Microsoft Word, Microsoft Excel, Agile Methodology, Amazon Web Services, Microsoft Azure, Cloud Computing, Encodings, Data Presentation, Django Web Framework, Machine Learning, Natural Language Processing, Power BI, Azure Machine Learning, Software Construction, SQL Databases, Tableau (Software), Data Processing, Test-Driven Development (TDD), Feature Engineering, ReactJS, Large Language Models, Prompt Engineering, Deep Learning, Model Validation, Generative AI, Git, Feature Selection, Machine Learning Operations, Front End Software Development, Docker, Databricks
- **Published:** August 11, 2026
- **Apply:** https://apply.deloitte.co.uk/UKCareers/Login?jobId=24608

## About the Role

* Strong problem solving skills.
 * Experience using Python (pandas, numpy, scikit-learn).
 * Solid understanding of the mathematical, probability and statistical principles behind Machine Learning models.
 * Experience using and deploying common machine learning algorithms (Supervised and unsupervised).
 * Good communication skills and data presentation skills, with the ability to build convincing recommendations and sell these to a non-technical audience.
 * End-to-end experience on at least one data science project: data wrangling, feature engineering, feature selection, model training, model validation.
 * Self-driven, able to work independently yet acts as a team player.
 * Able to apply data science principles through a business lens.

Desirable

 * Experience using R.
 * Familiar with, preferably experienced in, Deep Learning (e.g. RNNs, CNNs) or NLP techniques (e.g. TF-IDF, word-embedding).
 * Understanding of Large Language Models, Generative AI frameworks, prompt engineering, fine tuning, resource augmentation.
 * Familiarity with / experienced in software engineering best practices. E.g. test-driven development, smart data structure and algorithm selection.
 * Experience in using cloud environment (e.g. Azure, AWS or equivalent).
 * Experience using Azure Databricks, Azure MLflow, Azure ML services and/or other ML services.
 * Experience working in a Dev/MLOps environment.
 * Experience using Git, Excel, SQL, PowerBI, Tableau.
 * Experience using Docker and Kubernetes.
 * Experience working in an Agile development team.
 * Front End development experience (e.g. React, Django).
 * Experience of delivery data science and machine learning projects for financial industry or large/complex organisations.



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