At Barclays, we pride ourselves on being a leader in the financial industry and are dedicated to maintaining the highest standards of integrity and security. As a Financial Crime Data Modeller, you will play a crucial role in our ongoing efforts to combat financial crime and protect our customers and business. We are seeking a highly skilled and motivated individual to join our team and help us stay ahead of constantly evolving threats. If you have a strong background in data analysis, risk management, and a passion for fighting financial crime, we would love to hear from you. Join us in shaping the future of financial security.
- Conduct data analysis and modeling to identify potential financial crime risks and trends within the organization.
- Develop and maintain financial crime risk models and algorithms to detect and prevent fraudulent activities.
- Collaborate with cross-functional teams to gather and analyze data from various sources to support financial crime risk assessments.
- Continuously monitor and evaluate the effectiveness of existing risk models and make recommendations for improvements.
- Stay up-to-date on industry trends and regulatory requirements related to financial crime and incorporate them into the risk models.
- Work closely with the compliance and fraud prevention teams to ensure alignment of strategies and risk management practices.
- Conduct regular reviews and audits of financial crime risk models to ensure accuracy and effectiveness.
- Communicate findings and recommendations to senior management and other stakeholders in a clear and concise manner.
- Identify and escalate any potential issues or vulnerabilities to the financial crime risk management program.
- Train and mentor junior team members on data modeling techniques and best practices for financial crime risk management.
Strong Background In Data Modelling And Statistical Analysis: A Financial Crime Data Modeller At Barclays Should Have A Deep Understanding Of Data Modelling Techniques And Statistical Analysis Methods To Effectively Analyze And Interpret Large Datasets Related To Financial Crime.
Knowledge Of Financial Crime Trends And Regulations: The Ideal Candidate Should Possess A Thorough Understanding Of Current Financial Crime Trends And Regulations In Order To Identify Potential Risks And Implement Effective Prevention Strategies.
Proficiency In Programming Languages And Data Manipulation Tools: A Financial Crime Data Modeller Should Be Proficient In Programming Languages Such As Sql, Python, And R, As Well As Data Manipulation Tools Like Tableau And Excel, To Efficiently Process And Analyze Large Datasets.
Excellent Communication And Presentation Skills: As A Key Member Of The Financial Crime Team, The Data Modeller Should Be Able To Effectively Communicate Complex Data Insights To Non-Technical Stakeholders And Present Findings To Senior Management.
Attention To Detail And Problem-Solving Skills: Attention To Detail Is Crucial In Financial Crime Data Modelling To Ensure Accuracy And Identify Potential Anomalies Or Patterns. The Candidate Should Also Possess Strong Problem-Solving Skills To Develop Innovative Solutions To Complex Data Challenges.
Data Analysis
Data Mining
Statistical modeling
Risk assessment
Risk Mitigation
Investigative skills
Fraud prevention
Fraud detection
Compliance monitoring
Pattern Recognition
Financial Crime Trend Analysis
Communication
Conflict Resolution
Emotional Intelligence
Leadership
Time management
creativity
Attention to detail
Teamwork
Adaptability
Problem-Solving
According to JobzMall, the average salary range for a Financial Crime Data Modeller in Glasgow, UK is between £35,000-£55,000 per year. However, this can vary depending on factors such as the specific company, experience level, and qualifications of the individual.
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Barclays plc is a British multinational investment bank and financial services company, headquartered in London. Apart from investment banking, Barclays is organised into four core businesses: personal banking, corporate banking, wealth management, and investment management.
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