Join us as a Fraud Prevention Data Scientist, Wealth and Retail You'll design and implement data science tools and methods which harness our data in order to protect the Wealth and Retail channel We'll look to you to actively participate in the data community to identify and deliver opportunities to support the bank's strategic direction and keep customers safe through better use of data This is an opportunity to promote data literacy education with business stakeholders supporting them to foster a data driven culture and to make a real impact with your work What you'll do As a Data Scientist, you'll bring together statistical, mathematical, machine-learning and software engineering skills to consider multiple solutions, techniques and algorithms to develop and implement ethically sound models end-to-end.
We'll look to you to understand the needs of business stakeholders, form hypotheses and identify suitable data and analytics solutions to meet those needs in order to maximise the protection for Wealth and Retail customers.
As well as this you'll be collaborating effectively across the Fraud CoE and Data Analytics teams, showcasing experiments, and sharing best practices and techniques by using repository tools such as Gitlab You'll also be: Using data translation skills to work closely with business stakeholders to define detailed business questions, problems or opportunities which can be supported through analytics Applying a software engineering and product development lens to business problems, creating, scaling and deploying software driven products and services Working in an Agile way within multi-disciplinary data and analytics teams to achieve agreed project and scrum outcomes Selecting, building, training and testing machine learning models considering model valuation, model risk, governance and ethics, making sure that models are ready to implement and scale Iteratively building and prototyping data analysis pipelines to provide insights that will ultimately lead to production deployment The skills you'll need You'll need a strong academic background in a STEM discipline such as Mathematics, Physics, Engineering or Computer Science.
You'll have experience with statistical modelling and machine learning techniques, as well as the ability to operate with a high degree of independence and feel comfortable working within a geographically distributed team.
We'll also look for you to have experience of developing Tableau or similar data visualisation dashboards to steer business priorities and performance within financial services knowledge, and an ability to identify wider business impact, risk or opportunities and make connections across key outputs and processes You'll also demonstrate: The ability to use data to solve business problems from hypotheses through to resolution Experience using programming language and software engineering fundamentals Experience of Cloud applications and options Experience in synthesising, translating and visualising data and insights for key stakeholders Experience of exploratory data analysis Good communication skills with the ability to proactively engage with a wide range of stakeholders