Fraud Data Analyst

1 semana atrás


Sao Paulo, Brasil Risk Solutions Tempo inteiro

LexisNexis Risk Solutions provides a full portfolio of Professional Services to expertly guide any business, of any size, through the design, implementation and ongoing optimization of best in class fraud, identity and authentication solutions.

Helping customers get the most out of their technology investment, the Engagement and Analytics team provides a range of services, from strategy optimization and consulting, to onsite support and Quarterly Business Reviews.

The Fraud Data Analyst works as part of a customer engagement team to support large banking, financial, and insurance customers in their deployment of fraud and identity solutions. This is primarily a consultant role with a technical and analytics bent.

**Responsibilities**:
- Review suspicious activity and complex fraud cases to identify new risks and issues- Analyze data in order to build and adjust rules that identify fraud, reduce friction, and regulate customer workflows in real-time- Deliver persuasive analyses to both technical and non-technical audiences - sometimes in-person at the customer site- Advise clients on best practices for their technical implementation and analysis of ThreatMetrix DDP and other LexisNexis Risk SolutionsBasic Qualifications- Native or fluent in English (Spanish is a plus)- Ability to travel up to 10%- Quantitative or technical degree- 2+ years of experience managing large customer-facing solutions- 2+ years of experience in financial services, banks, or insurance organizations- 2+ years of experience delivering analytics using tools such as Python (pandas, sklearn, matplotlib) or R- Demonstrated competence using SQL and Excel for reports- Willingness to conduct root-cause analysis of client’s issues and learn new products- Motivated to help customers succeed and deliver value through proof-of-concept analysis

Desired Experience- Experience investigating financial crimes and fraud - account takeover, card not present, money laundering, social engineering etc.- Knowledge or research involving cybersecurity - browser-fingerprinting, public key infrastructure, computer networking, device authentication etc.- Experience in statistical/scorecard modeling or graph analysis to deliver insights - especially as it pertains to credit risk or fraud detection

About LexisNexis Risk Solutions

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