Asset & Liability Management Data Scientist
Join us as an Asset & Liability Management Data Scientist.
- In this role, you'll drive and embed the design and implementation of data science tools and methods for use in managing the bank's non-traded interest rate risk.
- Day-to-day, you'll act as a subject matter expert and articulate advanced data and analytics opportunities, bringing them to life through data visualisation.
- If you're ready for a new challenge and want to apply your data science expertise in a commercial setting for a top tier UK bank, this could be the role for you.
- You'll enjoy an inclusive working environment where diversity is celebrated.
What you'll do
We're looking for someone to understand the requirements and needs of both the Asset & Liability Management team and the business stakeholders the team supports. You'll develop good relationships within Treasury and across the businesses, form hypotheses, and identify suitable data and analytics solutions to meet their needs and deliver the team's strategy.
You'll be maintaining and developing external curiosity covering emerging trends within data science, data architecture development within the bank and contributing to the effective management of the bank's exposure to interest rates, ensuring that any risks to our £12bn net interest income revenue are identified and managed.
You'll also be responsible for:
- Proactively bringing together statistical, mathematical, machine-learning and software engineering skills to consider multiple solutions, techniques, and algorithms.
- Model building and data management, increasing the bank's use of automated product hedging solutions for existing and new franchise customer products.
- Selecting, building, training, and testing complex machine models, considering model valuation, model risk, governance, and ethics throughout to implement and scale models.
- Producing and analysing interest rate risk metrics such as IRRBB.
The skills you'll need
To be successful in this role, you'll hold an undergraduate or postgraduate degree in a Data Science discipline.
You'll need to have proficiency with Python and SQL, and experience in using data from cloud environments and applying machine learning on large data sets. And we'll look to you to bring the ability to demonstrate self-direction and a willingness to both teach others and learn new techniques.
Additionally, you'll need:
- Experience of articulating and translating questions and using statistical techniques to arrive at an answer using available data.
- Effective verbal and written communication skills and the ability to adapt your communication style to a specific audience.
Hours: 35
Ways of Working: Hybrid
