You will partner with world-renowned clients, helping them to leverage the power of their data to solve their most complex business challenges.
You will be part of a market-leading team, bringing together people and insights from a variety of sources and backgrounds.
You will work on cutting edge projects where no two days are the same, accelerating your learning and allowing you to progress more quickly.
Are you looking to return to the workplace after an extended career break?
For this role we can offer coaching and support designed for returners to refresh your knowledge and skills, and help your transition back into the workplace after a career break of 2 years or more.
If this is relevant for you, just let your recruiter know when you make your application.
We are looking to expand our team by the hiring of focused, aspirational and collaborative practitioners, and as such we are offering the opportunity to join as a Data Science and Machine Learning Manager to support this challenging and rapidly expanding business.
Deloitte offers a unique career opportunity in a supportive, challenging and fast-growth environment.
The successful candidate will have responsibility for delivery across a range of Financial Services analytics offerings, including :
Providing data analytics / data science services through the use of software such as Python / R, Azure, Databricks / other ML services, SQL, Tableau, Power BI to deliver meaningful insights to our clients and help them to understand the risks and key drivers for their business.
Reviewing existing internal and third-party data science and cloud solutions.
Development and delivery of new and innovative data science and machine learning tools and solutions to support evolving audit and assurance needs.
Helping the team to support our clients in all areas of large data handling, manipulation, analysis and modelling.
Working effectively in diverse teams within an inclusive team culture where people are recognized for their contribution.
Your work, your choice
At Deloitte we believe the best impact is the value we add, not the hours we sit at our desk. We carefully consider agile ways of working, both formal and informal, that allow for the best impact for our people and our clients.
Please speak to your recruiter about the working pattern that works best for you.
Location : London office with occasional domestic and international travel and an option of working from home or other offices when appropriate, even after Covid period.
Work pattern : This is a permanent full-time role.
Your professional experience
BS, MS or PhD in Engineering, Statistics, Computer Science, or Data Sciences (or equivalent experience).
Strong problem solving skills, and capable of generating original solutions to real-world problems.
Experience of coaching junior data scientists / analysts.
Experience in reviewing code and documentation to a high standard.
3+ years’ experience using Python (pandas, numpy, scikit-learn).
6+ years’ end-to-end experience of managing multiple data science and analytics projects in different industries and with different types of data (text, numerical, categorical).
2+ years’ project management experience in a DevOps environment.
Experience in using cloud environment (e.g. Azure, AWS).
Solid understanding of mathematics, probability and statistics.
Deep knowledge in a range of machine learning techniques.
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; able to apply data science principles through a business lens.
Experience using R.
Familiar with, preferably experienced in, Deep Learning (e.g. RNNs, CNNs) or NLP techniques (e.g. TF-IDF, word-embedding).
Experience of exercising software engineering best practices. E.g. test-driven development, smart data structure and algorithm selection.
Experience in using cloud environment (e.g. Azure, AWS)..
Experience working in a Dev / MLOps environment.
Experience using Azure Databricks, Azure MLflow, Azure ML services and / or other ML services.
Experience using Git, Excel, SQL, PowerBI, Tableau.
Experience using Docker and Kubernetes.
Experience working in an Agile development team.
Experience delivery data science and machine learning projects for financial industry or large / complex organisations.