This role will be within the Digital Identity Sub-Value Stream (DI SVS). DI SVS is focused on identifying and working with some of the most interesting external vendors from around the world to provide cutting edge products to the wider bank and our more than 40 million global customers.
responsibilities :
Collaborate with data scientists, engineers, and stakeholders to define project requirements and deliverables
Define and maintain model development best practices and standards
Evaluate and select appropriate algorithms and techniques for various machine learning applications
Perform data exploration and analysis to identify relevant features and patterns
Conduct model performance evaluation and optimization to ensure accuracy and efficiency
Develop and maintain model deployment and monitoring pipelines
Identify and mitigate potential model bias or ethical concerns
Provide training and documentation to end-users and stakeholders
Keep up-to-date with the latest advancements in machine learning and data science
requirements-expected :
Bachelors or Masters degree in computer science, data science, or a related field
Solid understanding of statistical analysis and data modeling concepts
Experience with data visualization tools such as Tableau or PowerBI
Programming skills in Python or R would be advantageous
Excellent problem-solving and analytical skills
Strong communication and collaboration skills
Ability to work in a fast-paced and dynamic environment
