Join us as a Data Scientist, Artificial Intelligence
* You'll be identifying and working with large, complex data sets to solve difficult, non-routine analysis problems, applying advanced analytical methods as needed
* We'll look to you to actively participate in the data community to identify and deliver opportunities to support the bank's strategic direction through better use of data
* This is an opportunity to achieve excellent exposure in a challenging role and to make a real impact with your work
What you'll do
As a Data Scientist, you'll be helping to detect and reduce fraud using machine learning, scientific rigour and advanced statistical methods. You'll be supporting and collaborating with multidisciplinary teams of data engineers and analysts on a wide range of business problems including the prevention of financial crime, understanding customer interactions with the bank and the management of credit risk.
You'll Also Be
* Developing and deepening your knowledge of data structures and model performance metrics, advocating for changes where needed for product development
* Communicating effectively across our functions and franchises to make business recommendations, gaining business buy-in to solutions tailored to customers' needs
* Conducting analysis that includes data gathering and requirements specification in collaboration with business stakeholders
* Iteratively building and prototyping data analysis pipelines to provide insights that will ultimately lead to production deployment
* Identifying new methods, tools, techniques and opportunities to deliver business value via cost reduction, income generation or improved customer experience through the application of data science
The skills you'll need
To succeed in this role, you'll need significant experience of developing and deploying supervised machine learning models, including classification algorithms, anomaly detection techniques, and network analysis methods. You'll be familiar with large language models (LLMs) and generative AI technologies.
You'll also need evidence of previous project implementation and work experience gained in a data analysis related field as part of a multidisciplinary team. Additionally, you'll hold a degree in a quantitative discipline or have evidence of equivalent practical experience.
You'll Also Demonstrate
* Sound knowledge of Python, SQL, version control (git) and familiarity with agile working practices
* Experience with big data technologies (Spark, Hadoop) and cloud environments (preferably AWS)
* Experience articulating and translating business questions and using statistical techniques to arrive at an answer using available data
* The ability to demonstrate leadership, self-direction and a willingness to both teach others and learn new techniques
* Excellent written and verbal communication skills and the ability to adapt the communication style to a specific audience
* Extensive relevant work experience, with emphasis on statistical data analysis such as linear models, multivariate analysis, stochastic models and sampling methods
* Experience with prompt engineering, fine-tuning, and integrating GenAI capabilities via APIs to deliver practical business solutions