About the Company
Barclays is a British universal bank, diversified by business, by different types of customers and clients, and by geography. Our businesses include consumer banking and payments, corporate and investment banking, and wealth management. For over 330 years, Barclays has been helping customers, clients, and communities prosper. We are committed to fostering innovation and maintaining the highest standards of security, leveraging advanced AI to combat financial crime and protect our valued customers.
Job Description
Join Barclays as an Anti-Fraud Data Labeler within our cutting-edge AI department, dedicated to enhancing our fraud detection capabilities. In this crucial role, you will be responsible for meticulously reviewing and labeling large datasets related to financial transactions, customer interactions, and suspicious activities. Your precision and attention to detail will directly contribute to the training and refinement of our machine learning models, empowering them to identify and prevent fraudulent behaviors more effectively. This is an on-site position at our Glasgow office, where you will work closely with data scientists and fraud analysts, providing the foundational data that protects our customers and the integrity of our banking systems.
Key Responsibilities
- Accurately label and annotate data points, including transaction details, customer profiles, and communication logs, for use in machine learning models.
- Identify and categorize various types of fraudulent activities and patterns as defined by project guidelines.
- Maintain high standards of data quality and consistency through diligent review and validation processes.
- Collaborate with data scientists and subject matter experts to understand labeling requirements and improve annotation guidelines.
- Provide feedback on data quality issues and tool functionalities to enhance the data labeling process.
- Adhere to strict data privacy and security protocols, handling sensitive financial information responsibly.
- Participate in regular training sessions to stay updated on fraud trends and labeling best practices.
Required Skills
- Exceptional attention to detail and strong analytical skills.
- Ability to process and categorize large volumes of information accurately and efficiently.
- Proficiency with computer systems and basic data entry tools.
- Strong organizational skills and ability to manage time effectively.
- Excellent communication skills, both written and verbal.
- High level of integrity and discretion when handling sensitive data.
- Ability to work effectively in a team-oriented environment.
Preferred Qualifications
- Previous experience in data entry, data annotation, or quality assurance.
- Familiarity with financial terminology or banking operations.
- Understanding of basic machine learning concepts or AI ethics.
- Experience with data labeling platforms or annotation tools.
- A keen interest in fraud prevention and data security.
Perks & Benefits
- Competitive annual salary and performance-based bonuses.
- Comprehensive health, dental, and vision insurance.
- Generous paid time off and holidays.
- Retirement savings plan with company match.
- Opportunities for professional development and career growth within a global banking institution.
- Access to employee wellness programs and resources.
- Employee discount programs on banking services and other offerings.
- On-site facilities including cafeteria and gym (where available).
How to Apply
If you are interested in this position, please click the "Apply Now" button below. To ensure your application is properly considered, please prepare the following:
- An up-to-date Resume or CV
- A brief cover letter summarizing your experience and motivation
Applications are reviewed on a rolling basis. Only shortlisted candidates will be contacted for an interview.
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