Barclays Hiring Graduates, Postgraduates: Check Essential Details

Overview:

Barclays is hiring eligible and interested applicants for the post of Director Data Analytics at their Noida, India location.

To complete details for this job are as follows.

Roles and Responsibilities:

• Management of design and production of analysis and monitoring to improve fraud detection rule strategies, responding to emerging trends and attack.
• Model Risk management for Fraud Models
• Data Governance in compliance with GDMS standards
• Representation of Fraud Analytics and Strategy in all forums conducted for platform/data migrations
• Leading the journey of FAST into new platforms and technology e.g. AWS
• Continuous exploration of new technologies like BitBucket, Tableau, etc. to complement FAST’s dynamic environment
• Overseeing Fraud operations services
• Stakeholder Management and Leadership
• Partnering closely with respective portfolio leads across BI, BUK and USCB providing them with required consultancy/support
• Partnering closely with CIO/CDO/FRAUD TECH/EDP for Design / Architecture, delivery planning of platforms for FAST
• Managing multiple functions across FAST – Analytics, Strategy, Data Governance, DOS, Model Risk, Operations

Person Specification

• Bachelor / Master’s degree
• Pioneering – High level of initiative/innovation
• Good attention to detail/hands on with excellent organizational skills
• To be successful in this role you should have experience with/able to lead:
• Strong Analytical skills and experience in analytics domain
• Strategic thought and change leadership
• Strong understanding of various data platforms and technologies
• Self-starter and ability to lead; successful track record in leading through influence
• Very strong people management and stakeholder management
• Ability to collaborate across teams to deliver complex systems and components and manage stakeholder’s expectations well

Purpose of the role:

• To implement data quality process and procedures, ensuring that data is reliable and trustworthy, then extract actionable insights from it to help the organisation improve its operation, and optimise resources.

Accountabilities:

• Investigation and analysis of data issues related to quality, lineage, controls, and authoritative source identification.
• Execution of data cleansing and transformation tasks to prepare data for analysis.
• Designing and building data pipelines to automate data movement and processing.
• Development and application of advanced analytical techniques, including machine learning and AI, to solve complex business problems.
• Documentation of data quality findings and recommendations for improvement.

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