Senior Fraud Analytics Lead — Payments & Risk

Early Warning Services LLC; United States; Hybrid; USD 104,000 - 156,000; Full time

Benefits offered by this job

Healthcare coverage

401(k) match

Paid time off

Parental leave

Maven Family Planning

Job summary

Early Warning Services LLC is seeking a seasoned fraud analytics professional to execute advanced data analyses and identify root causes of fraud events across our payments network. You will translate complex insights into actionable remediation strategies for participating financial institutions.

The role emphasizes cross-functional collaboration, strong communication skills, and hands-on work with SAS/SQL/R/Python to model and monitor risk. Hybrid work is offered with a focus on collaboration.

Qualifications

• Bachelor’s degree required or equivalent.
• Minimum 5+ years of progressive data analytics experience.
• 3+ years SAS/SQL/R/Python or comparable analytic coding experience.
• Exceptional written and verbal communication skills.
• Experience with digital banking, payments and/or payment networks.
• Background check and drug screen.

Responsibilities

• Identify root causes of fraud events in the network and categorize them.
• Develop fraud analyses to source, analyze, and deduce root causes across the network.
• Articulate findings and influence actions with stakeholders at participating financial institutions.
• Identify exposed network credentials, social tokens and payment data; categorize risk and apply appropriate treatments.
• Support the integrity and confidentiality of systems and data.

Skills

Data analytics

Communication skills

Fraud analytics

Education

Bachelor's Degree

Tools

SAS/SQL/R/Python

Job description

Early Warning Services LLC is seeking a seasoned fraud analytics professional to execute advanced data analyses and identify root causes of fraud events across our payments network. You will translate complex insights into actionable remediation strategies for participating financial institutions.

The role emphasizes cross-functional collaboration, strong communication skills, and hands-on work with SAS/SQL/R/Python to model and monitor risk. Hybrid work is offered with a focus on collaboration.