Data Scientist AI/ML

To be successful in this role, you should possess the following skillsets:

1. Python Programming.
2. Knowledge of Artificial Intelligence and Machine Learning algorithms including NLP.
3. SQL.
4. Spark/PySpark.
5. Predictive Model development.
6. Model lifecycle and model management including monitoring, governance and implementation.
7. DevOps tools like Git/Bitbucket etc.
8. Project management using JIRA.

Some other highly valued skills include:

1. DevOps tools TeamCity, Jenkins etc.
2. Knowledge of Financial/Banking Domain.
3. Knowledge of GenAI tools and working.
4. AWS.
5. Databricks.

Purpose of the role

To design, develop, implement, and support mathematical, statistical, and machine learning models and analytics used in business decision-making

Accountabilities

1. Design analytics and modelling solutions to complex business problems using domain expertise.
2. Collaboration with technology to specify any dependencies required for analytical solutions, such as data, development environments and tools.
3. Development of high performing, comprehensively documented analytics and modelling solutions, demonstrating their efficacy to business users and independent validation teams.
4. Implementation of analytics and models in accurate, stable, well-tested software and work with technology to operationalise them.
5. Provision of ongoing support for the continued effectiveness of analytics and modelling solutions to users.
6. Demonstrate conformance to all Barclays Enterprise Risk Management Policies, particularly Model Risk Policy.
7. Ensure all development activities are undertaken within the defined control environment.