
Data Driven Fraud Prevention Specialist
4 days ago
Fraud data analysis is a critical component of modern business operations. In this role, you will be responsible for developing and deploying predictive analytics models and machine learning algorithms to identify suspicious activities and patterns in financial transactions.
The ideal candidate will have expertise in designing and implementing complex statistical models, as well as experience with fraud detection systems and machine learning platforms.
- Design and deploy predictive analytics models and machine learning algorithms to identify suspicious activities and patterns.
- Continuously optimize fraud monitoring systems to improve detection accuracy and reduce false positives.
- Analyze internal and external data sources to identify vulnerabilities and recommend proactive measures.
- Define and track key performance indicators (KPIs) to measure the effectiveness of fraud detection strategies.
We are looking for a candidate with a Master's degree in data science, statistics, economics, business administration, or a related field, and at least 10 years of experience in fraud analytics, risk management, or data analytics.
- Master's degree in data science, statistics, economics, business administration, or a related field.
- At least 10 years of experience in fraud analytics, risk management, or data analytics.
- Expertise in designing and implementing complex statistical models.
- Experience with fraud detection systems and machine learning platforms.
This is an exciting opportunity to work with a talented team and make a real impact on our business.
As a Fraud Data Analyst, you will have the opportunity to work closely with risk management, compliance, IT, and other departments to ensure alignment and effective communication.
OthersThe ideal candidate will have proven track record of developing and implementing fraud detection systems, experience with market intelligence tools and competitive analysis, expertise in data analytics tools (e.g., Python, R, SQL, SAS), familiarity with machine learning platforms and fraud detection software, and knowledge of industry-specific regulations and compliance standards.
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