Job description

Join us as a Data Scientist

Playing a key role in advancing applied AI and AI research within the financial services industry, you’ll work within a team of skilled data scientists to tackle complex business challenges using advanced analytics and machine learning techniques

You’ll be supporting the development, deployment, and maintenance of advanced machine learning models and algorithms, including large models

This is an opportunity to make a significant impact with us and establish yourself as a prominent contributor in the field of data science and AI

What you'll do

As a Data Scientist, you'll be responsible for contributing to the development and execution of innovative AI and data science solutions for the bank's most pressing challenges. You'll work within a team of data scientists and engineers, providing technical expertise while collaborating with cross-functional teams and stakeholders to deliver high-impact results.

Your Responsibilities Will Include

Supporting the data science community of practice, staying informed in the field of applied AI and AI research

Communicating effectively with stakeholders, providing insights and recommendations based on your team's projects and findings

Participating in end-to-end project delivery, from ideation to production deployment, ensuring alignment with business objectives

Assisting in the identification and implementation of cutting-edge technologies, tools and techniques to deliver value through cost reduction, income , or improved customer experience

The skills you'll need

To excel in this role as a Data Scientist, you'll need a solid academic background in a STEM discipline such as Mathematics, Physics, Engineering, or Computer Science, ideally with a MSc or PhD. You'll also need experience with statistical modelling and machine learning techniques, as well as some knowledge of financial services.

In Addition, You'll Demonstrate

The ability to use data to solve business problems from hypotheses through to resolution

Expertise in key data science technologies and techniques, such as Python, Git, AWS, AWS SageMaker, PyTorch, TensorFlow, JAX, NumPy, scikit-learn, time-series forecasting, classification, regression, large- models, and experimental design

Experience of using programming and software engineering fundamentals

Experience of exploratory data analysis

Effective communication skills with the ability to proactively engage with a wide range of stakeholders

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