Senior Fraud Decision Science Analyst at Radial in King Of Prussia, PA
Job
Summary:
As a Senior Fraud Decision Science Analyst, you will be responsible for identifying new and unique ways of finding and capturing ecommerce fraud trends. This role is a terrific opportunity to work in the dynamic space of e-commerce fraud to solve complex problems using big data technologies. This role will work alongside a team of analysts and data scientists. The department uses a wide variety of systems, tools and algorithms to evaluate data, execute their investigation and develop an efficient analytical workflow including machine learning models, velocity detection and behavior analytics. Position
Responsibilities:
Analyze large volume of data using big data technologies to detect the fraud trends proactively. Create the fraud business rules for deployment in case management engine to increase auto-decision rate and reduce manual review and chargeback rate. Conduct portfolio analytics to generate client insights, market segmentation, and measure clients' risk profile. Conduct robust analysis to help create rules and processes to proactively mitigate fraud and reduce customer impact. Evaluate, resolve, and respond to fraud impacts to clients via analysis Work with 3rd party vendors to enhance analytics and improve data capabilities for analysis Support the Fraud Analytics, Order Review, and Chargeback teams, and work closely with other internal and external technology groups Required Skills and
Experience:
Bachelor's degree in Criminal Justice or a quantitative discipline. Master's degree is preferred. 8
years of working experience in fraud decisioning and fraud review Strong programming skills in SQL, and Microsoft 365 Tools (Excel, Word, Power Point, Etc) required Experiences with Python and Tableau strongly desired Understanding Machine Learning and modeling is a plus Strong analytical, organizational and communication skills
Salary Range:
$80K -- $100K
Minimum Qualification
Risk & Quantitative AnalysisEstimated Salary: $20 to $28 per hour based on qualifications.
Summary:
As a Senior Fraud Decision Science Analyst, you will be responsible for identifying new and unique ways of finding and capturing ecommerce fraud trends. This role is a terrific opportunity to work in the dynamic space of e-commerce fraud to solve complex problems using big data technologies. This role will work alongside a team of analysts and data scientists. The department uses a wide variety of systems, tools and algorithms to evaluate data, execute their investigation and develop an efficient analytical workflow including machine learning models, velocity detection and behavior analytics. Position
Responsibilities:
Analyze large volume of data using big data technologies to detect the fraud trends proactively. Create the fraud business rules for deployment in case management engine to increase auto-decision rate and reduce manual review and chargeback rate. Conduct portfolio analytics to generate client insights, market segmentation, and measure clients' risk profile. Conduct robust analysis to help create rules and processes to proactively mitigate fraud and reduce customer impact. Evaluate, resolve, and respond to fraud impacts to clients via analysis Work with 3rd party vendors to enhance analytics and improve data capabilities for analysis Support the Fraud Analytics, Order Review, and Chargeback teams, and work closely with other internal and external technology groups Required Skills and
Experience:
Bachelor's degree in Criminal Justice or a quantitative discipline. Master's degree is preferred. 8
years of working experience in fraud decisioning and fraud review Strong programming skills in SQL, and Microsoft 365 Tools (Excel, Word, Power Point, Etc) required Experiences with Python and Tableau strongly desired Understanding Machine Learning and modeling is a plus Strong analytical, organizational and communication skills
Salary Range:
$80K -- $100K
Minimum Qualification
Risk & Quantitative AnalysisEstimated Salary: $20 to $28 per hour based on qualifications.
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