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To design, develop, implement, and support mathematical, statistical, and machine learning models and analytics used in business decision-making
Job Responsibility:
Drive technical architecture with technology with a keen focus on DevOps and automation across the model development & deployment life-cycle
Build & maintain analytical frameworks that promote the re-use of model calculation across multiple business use-case (e.g IFRS9, CECL, Stress testing)
Work with data scientists & quantitative model developers to drive strategic initiatives and deliver innovative financial models used for risk reporting and capital adequacy
Collaborate with Tech and Quantitative teams globally to develop and refine data science infrastructure in Python while driving the Modelling Data Strategy to support both model development and execution needs
Partner with technology to build scalable, data and analytics platforms that can connect to internal systems for pricing and/or reporting systems
Supervise a team of quantitative developers to build analytics by using distributed computing solutions in python
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
Requirements:
A bachelor’s or master’s degree in computer science, engineering or related technical fields
Expertise in python software development, with a depth in developing concurrent software solutions in its ecosystem
Ability to decompose complex problems into practical and operational solutions with proven experience of leading teams
Excellent communicator and team player, possessing board managerial, critical problem solving, debugging and troubleshooting skills
Expertise in stakeholder management across business & technology partners with a proven ability to deliver according to the agreed timelines
Experience in MLOps is preferred along with DevOps tools such as Git, TeamCity
Experience with frameworks like kedro, mflow and platforms like databricks a plus
Experience in developing frameworks for mathematical, statistical, and machine learning models and analytics used in financial institution preferred
Nice to have:
Experience in MLOps is preferred along with DevOps tools such as Git, TeamCity
Experience with frameworks like kedro, mflow and platforms like databricks a plus
Experience in developing frameworks for mathematical, statistical, and machine learning models and analytics used in financial institution preferred
What we offer:
Hybrid working
Structured approach to hybrid working with fixed 'anchor' days
Supportive and inclusive culture and environment
Commitment to flexible working arrangements
International scale offering incredible variety, depth and breadth of experience
Chance to learn from a globally diverse mix of colleagues