Role Overview
The Data Science and Machine Learning Manager supports Deloitte's Audit and Assurance analytics offerings by delivering data insights, developing innovative tools, and leading teams in large data handling and modeling.
Responsibilities
* Providing data analytics/data science services to deliver meaningful insights to clients using Python, R, Azure, Databricks, SQL, Tableau, Power BI.
* Developing and delivering new data science and machine learning tools and solutions to support evolving audit and assurance needs.
* Helping the team support clients in large data handling, manipulation, analysis, and modeling.
* Working effectively in diverse teams within an inclusive team culture where people are recognized for their contribution.
Essential Qualifications
* Strong problem‑solving skills, and capable of generating original solutions to real‑world problems.
* Experience coaching junior data scientists/analysts.
* Experience reviewing code and documentation to a high standard.
* Experience using Python (pandas, numpy, scikit‑learn).
* End‑to‑end experience of managing multiple data science and analytics projects in different industries and with different types of data.
* Project management experience in a DevOps environment.
* Experience using cloud environments (Azure, AWS).
* Experience using Git.
* Solid understanding of mathematics, probability, and statistics.
* Deep knowledge of a range of machine learning techniques (Supervised and unsupervised).
* Understanding of Large Language Models, Generative AI frameworks, prompt engineering, fine tuning, resource augmentation.
* Strong communication and data presentation skills with the ability to build convincing recommendations and sell these to a non‑technical audience.
* Self‑driven, able to work independently yet acts as a team player.
* Ability to apply data science principles through a business lens.
Desirable Skills
* Experience using R.
* Familiar with Deep Learning (e.g. RNNs, CNNs) or NLP techniques.
* Experience developing Generative AI projects.
* Experience exercising software engineering best practices such as test‑driven development, smart data structure and algorithm selection.
* Experience using Azure Databricks, Azure MLflow, Azure ML services and/or other ML services.
* Experience using Excel, SQL, Power BI, Tableau.
* Experience using Docker and Kubernetes.
* Experience working in an Agile development team.
* Experience delivering data science for the financial industry or large/complex organizations.
Working Location
Based in London with hybrid working. You will have the opportunity to work in the local office, virtual collaboration spaces, client sites, and remotely as per role requirements.
Return to Work
For candidates returning after a career break of two years or more, we offer coaching and support designed to refresh your knowledge and skills and aid transition back into the workplace.
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