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Job details
Job ID
JR-0000095341
Job description
Job Description
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.
Vice President Expectations
To contribute or set strategy, drive requirements and make recommendations for change. Plan resources, budgets, and policies; manage and maintain policies/ processes; deliver continuous improvements and escalate breaches of policies/procedures..
If managing a team, they define jobs and responsibilities, planning for the department’s future needs and operations, counselling employees on performance and contributing to employee pay decisions/changes. They may also lead a number of specialists to influence the operations of a department, in alignment with strategic as well as tactical priorities, while balancing short and long term goals and ensuring that budgets and schedules meet corporate requirements..
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 will be a subject matter expert within own discipline and will guide technical direction. They will lead collaborative, multi-year assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialisation to complete assignments. They will train, guide and coach less experienced specialists and provide information affecting long term profits, organisational risks and strategic decisions..
Advise key stakeholders, including functional leadership teams and senior management on functional and cross functional areas of impact and alignment.
Manage and mitigate risks through assessment, in support of the control and governance agenda.
Demonstrate leadership and accountability for managing risk and strengthening controls in relation to the work your team does.
Demonstrate comprehensive understanding of the organisation functions to contribute to achieving the goals of the business.
Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategies.
Create solutions based on sophisticated analytical thought comparing and selecting complex alternatives. In-depth analysis with interpretative thinking will be required to define problems and develop innovative solutions.
Adopt and include the outcomes of extensive research in problem solving processes.
Seek out, build and maintain trusting relationships and partnerships with internal and external stakeholders in order to accomplish key business objectives, using influencing and negotiating skills to achieve outcomes.
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.
Join us as a “Data Scientist - Markets Sales Technology” at Barclays, where you'll spearhead the evolution of our digital landscape, driving innovation and excellence. You'll harness cutting-edge technology to revolutionise our digital offerings, ensuring unapparelled customer experiences.
You may be assessed on the key critical skills relevant for success in role, such as experience with, skills to meet business requirement as well as job-specific skillsets.
To be successful as a “Data Scientist - Markets Sales Technology”, you should have experience with:
Basic/ Essential Qualifications:
Designing, developing, and deploying advanced analytics and Machine Learning solutions across Markets use cases such as pricing, risk, forecasting, client analytics, liquidity, operational efficiency, or surveillance.
Identification, collection, extraction, and preparation of data from diverse internal and external sources, ensuring high data quality and analytical integrity.
Building and maintaining scalable data pipelines and analytical workflows in partnership with Data Engineering and Platform teams.
Developing predictive, statistical, and machine learning models and translating analytical outputs into actionable business insights.
Applying GenAI techniques such as natural language processing, document intelligence, retrieval‑augmented generation (RAG), and decision‑support use cases.
Strong stakeholder engagement with senior business, technology, risk, and control partners, with the ability to communicate complex concepts clearly and influence outcomes.
Operating effectively in regulated, enterprise environments with strong awareness of data governance, model risk management, and control frameworks.
Leading complex, cross‑functional initiatives and guiding other data scientists and specialists as a senior individual contributor or technical lead.
Desirable skillsets/ good to have:
Experience within Banking, Finance, or Capital Markets environments.
Strong programming skills in Python and SQL, with experience using modern analytics and machine learning frameworks.
Hands‑on experience delivering analytics or ML solutions into production environments, including performance monitoring and lifecycle management.
Familiarity with Enterprise Data Platforms, cloud‑based analytics ecosystems, and MLOps / AI governance practices.
Ability to balance strategic thinking with hands‑on technical execution.
