Data Scientist - Machine Learning Engineer

Purpose of the role

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

Accountabilities

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

Analyst Expectations

• To perform prescribed activities in a timely manner and to a high standard consistently driving continuous improvement.
• Requires in-depth technical knowledge and experience in their assigned area of expertise
• Thorough understanding of the underlying principles and concepts within the area of expertise
• They lead and supervise a team, guiding and supporting professional development, allocating work requirements and coordinating team resources.
• If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L – Listen and be authentic, E – Energise and inspire, A – Align across the enterprise, D – Develop others.
• OR for an individual contributor, they develop technical expertise in work area, acting as an advisor where appropriate.
• Will have an impact on the work of related teams within the area.
• Partner with other functions and business areas.
• Takes responsibility for end results of a team’s operational processing and activities.
• Escalate breaches of policies / procedure appropriately.
• Take responsibility for embedding new policies/ procedures adopted due to risk mitigation.
• Advise and influence decision making within own area of expertise.
• Take ownership for managing risk and strengthening controls in relation to the work you own or contribute to. Deliver your work and areas of responsibility in line with relevant rules, regulation and codes of conduct.
• Maintain and continually build an understanding of how own sub-function integrates with function, alongside knowledge of the organisations products, services and processes within the function.
• Demonstrate understanding of how areas coordinate and contribute to the achievement of the objectives of the organisation sub-function.
• Make evaluative judgements based on the analysis of factual information, paying attention to detail.
• Resolve problems by identifying and selecting solutions through the application of acquired technical experience and will be guided by precedents.
• Guide and persuade team members and communicate complex / sensitive information.
• Act as contact point for stakeholders outside of the immediate function, while building a network of contacts outside team and external to the organisation.

All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship – our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset – to Empower, Challenge and Drive – the operating manual for how we behave.

As a Data Scientist - Machine Learning Engineer at Barclays in the Financial Crime Unit, you will develop, optimise and deploy advanced machine learning models that will help identify suspicious financial activities, detect fraud and enhance security measures. You will be responsible for building and operating machine learning systems that function at scale, ensuring their performance, reliability and accuracy in real-world applications.

To be successful as a Data Scientist - Machine Learning Engineer, you should have experience with:

• Previous experience in deploying, maintaining and scaling machine learning models in production environments. Familiarity with CI/CD pipelines for Machine learning models.

• Excellent knowledge of AWS cloud services, especially for machine learning (e.g. AWS SageMaker, AWS Lambda, S3 and EC2) to facilitate deployment, monitoring and scaling.

• Proficiency in building machine learning models using Python, R, or similar languages and frameworks (e.g., scikit-learn, TensorFlow, PyTorch).

Some other highly valued skills may include:

• Results-oriented, with a passion for applying machine learning to tackle real-world problems and enhance financial security.

• Ability to work effectively in a collaborative, cross-functional team environment, with excellent communication skills to work with both technical and non-technical stakeholders.

You may be assessed on the key critical skills relevant for success in role, such as risk and controls, change and transformation, business acumen strategic thinking and digital and technology, as well as job-specific technical skills.

This role will be located at our London office.