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Financial Crime Analytics Officer(m/w/x)
Developing data-driven models for fraud detection on secure digital platforms. Minimum 2 years fraud prevention/AML experience required. Collaboration with stakeholders, SQL and Python/R proficiency.
Requirements
- Minimum 2 years fraud prevention/AML experience
- BS/MS in Computer Science, Mathematics, Statistics, Engineering, or related field
- Proficiency in SQL and Python/R
- Experience with large datasets and models
- Knowledge of financial crime typologies
- Excellent communication skills
- Team-oriented and collaborative
- Strong problem-solving and proactive mindset
- Experience with ML for fraud detection
- Familiarity with real-time transaction monitoring
- Understanding of web traffic and RESTful APIs
- Knowledge of AML/CTF and Fraud regulations
- Experience with data visualization tools
- Fluent English
- French and/or German (nice to have)
Tasks
- Develop data-driven models for fraud detection
- Implement and optimize fraud prevention models
- Analyze large datasets to identify suspicious patterns
- Detect anomalies and emerging fraud typologies
- Collaborate with stakeholders to translate business needs
- Build and maintain fraud monitoring dashboards
- Create reports and KPIs to track fraud trends
- Continuously improve detection strategies
- Balance fraud risk and false positives
- Support fraud investigations with data insights
- Communicate findings to technical and non-technical stakeholders
- Document processes and methodologies
- Ensure clear understanding of projects and workflows
- Stay updated on new fraud schemes
- Follow regulatory expectations and industry best practices
Work Experience
- 2 years
Education
- Bachelor's degree
Languages
- English – Native
- French – Basic
- German – Basic
Tools & Technologies
- SQL
- Python
- R
- Tableau
- Power BI
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Financial Crime Analytics Officer(m/w/x)
Developing data-driven models for fraud detection on secure digital platforms. Minimum 2 years fraud prevention/AML experience required. Collaboration with stakeholders, SQL and Python/R proficiency.
Requirements
- Minimum 2 years fraud prevention/AML experience
- BS/MS in Computer Science, Mathematics, Statistics, Engineering, or related field
- Proficiency in SQL and Python/R
- Experience with large datasets and models
- Knowledge of financial crime typologies
- Excellent communication skills
- Team-oriented and collaborative
- Strong problem-solving and proactive mindset
- Experience with ML for fraud detection
- Familiarity with real-time transaction monitoring
- Understanding of web traffic and RESTful APIs
- Knowledge of AML/CTF and Fraud regulations
- Experience with data visualization tools
- Fluent English
- French and/or German (nice to have)
Tasks
- Develop data-driven models for fraud detection
- Implement and optimize fraud prevention models
- Analyze large datasets to identify suspicious patterns
- Detect anomalies and emerging fraud typologies
- Collaborate with stakeholders to translate business needs
- Build and maintain fraud monitoring dashboards
- Create reports and KPIs to track fraud trends
- Continuously improve detection strategies
- Balance fraud risk and false positives
- Support fraud investigations with data insights
- Communicate findings to technical and non-technical stakeholders
- Document processes and methodologies
- Ensure clear understanding of projects and workflows
- Stay updated on new fraud schemes
- Follow regulatory expectations and industry best practices
Work Experience
- 2 years
Education
- Bachelor's degree
Languages
- English – Native
- French – Basic
- German – Basic
Tools & Technologies
- SQL
- Python
- R
- Tableau
- Power BI
Like this job?
BetaYour Career Agent finds similar jobs for you every day.
About the Company
Swissquote
Industry
FinancialServices
Description
The company is the Swiss leader in online banking, providing trading, investing, and banking services to over 500,000 clients.
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