Remote Senior New-Account Fraud Analytics Lead

Ladders; United States; Remote; USD 122,000 - 262,000; Full time

Benefits offered by this job

Remote work flexibility

Job summary

Ladders is seeking a Senior Quantitative Manager (New Account Screening) for a remote US-based role. You will lead analytics efforts supporting new account screening, focusing on fraud trend identification and stronger digital controls.

You will guide a team of analytics professionals and partner with cross-functional teams to improve screening strategy and reporting. The role combines statistical modeling, programming, and leadership to strengthen risk decisioning and support broader fraud

Qualifications

• Advanced degree in quantitative analytics, economics, statistics, engineering, or related field.
• 5-10 years of experience in analytics or fraud management.
• 2-4 years of management experience with leadership skills.
• 4-8 years of programming in SAS, R, and/or Python.
• 4-8 years of experience in statistical modeling and database management.

Responsibilities

• Lead a team focused on analytics and strategy for new account screening.
• Design and implement analytics to enhance digital account controls.
• Utilize descriptive and predictive analytics to address fraud trends.
• Manage reporting and strategy functions with independence.
• Mentor junior analytics professionals to develop their skills.
• Collaborate with cross-functional teams on fraud strategy initiatives.
• Provide ad hoc support for various analytics requests.

Skills

Leadership

Analytical thinking

Statistical modeling

Education

Advanced degree in quantitative analytics/economics/statistics/engineering

Tools

SAS

R

Python

Job description

Ladders is seeking a Senior Quantitative Manager (New Account Screening) for a remote US-based role. You will lead analytics efforts supporting new account screening, focusing on fraud trend identification and stronger digital controls.

You will guide a team of analytics professionals and partner with cross-functional teams to improve screening strategy and reporting. The role combines statistical modeling, programming, and leadership to strengthen risk decisioning and support broader fraud