The fraud data analyst works as part of a customer engagement team to support large E-commerce, Telecomm, Media, and Healthcare customers in their deployment of fraud and identity solutions. This is primarily a consultant role with a technical and analytics client facing focus.
Location: San Jose, CA (preferred)
Alternative: U.S. based remote worker (optional)
Travel: 20% year
High Level Overview:
- Review suspicious activity and complex fraud cases to help identify and resolve fraud risk trends and issues
- Clearly and thoroughly document investigation findings and conclusions
- Understand how to write rules in LexisNexis decision engines and manage customer risk policy, leveraging hundreds of signals in LexisNexis Digital Identity Network and data fed directly into the network by our customers
- Offline analyses of customer data to tune rules, exposes patterns, research anomalies, reduce false positives, and build executive and project-level reports
- Identify meaningful insights from chargeback data
- Interpret and communicate findings from analysis to engineers, product and stakeholders
- Analyze high-volume data to investigate, identify and report trends linked to fraudulent transactions
- Collaboration with LexisNexis teams including Products, Engineering, and your colleagues to continually redefine best practices by enhancing tools, data sources, system functionalities, and fraud detection methods
- Educate internal team members and external parties on processes and procedures
- Demonstrate a professional and customer-centric persona when interacting directly with merchants and customers via on-site visits, phone, e-mail, and chat
- Risk and Technology consulting; sharing best practices with fraud managers, risk analysts, application developers, and project managers for combating persistent and emerging security threats
- 2+ years of data analytics experience
- Demonstrated proficiency using SQL and Excel
- Demonstrated competence in research and problem resolution
- Strong organization, prioritizing, and time management skills
- Customer success mindset and effective communication
- Experience in managing large customer-facing solutions
- Knowledge of cybercrime -- account takeover, Card not Present, money laundering, social engineering etc.
- Knowledge of cybersecurity - browser-fingerprinting, public key infrastructure, IP spoofing, device authentication etc.
- Experience in statistical modeling and/or scorecard development
- Experience with data science toolkit -- Python (pandas, sklearn), R, SAS
- Quantitative degree preferred
We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. If a qualified individual with a disability or disabled veteran needs a reasonable accommodation to use or access our online system, that individual should please contact firstname.lastname@example.org or if you are based in the US you may also contact us on 1.855.833.5120.
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