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 language 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 generation, 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-language models, and experimental design
Experience of using programming language 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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