Senior Analyst, Fraud Intelligence

Ladders; United States; Remote; USD 125,000 - 145,000; Full time

Benefits offered by this job

Medical benefits

Dental benefits

Vision benefits

Stock options

Paid time off

401(k) plan guidance

Job summary

Ladders is seeking a Senior Analyst, Fraud Intelligence to uncover fraud signals across large data environments and translate findings into practical mitigations. You will partner with machine learning, operations, and stakeholders to strengthen risk controls in a remote role within the United States.

This position blends hands-on data analysis with strategic input on monitoring frameworks, review processes, and model features.

Qualifications

• 3+ years of experience in fraud analytics, preferably in e-commerce or retail.
• Bachelor's degree in Mathematics, Statistics, or Computer Science.
• Strong understanding of data science concepts, including statistical analysis and modeling.
• Proficiency in SQL and experience with Python libraries such as pandas, NumPy, and scikit-learn.
• Exceptional communication skills with a proven ability to influence cross-functional teams.
• Experience with automated decisioning systems is a plus.
• High attention to detail and strong intellectual curiosity.

Responsibilities

• Analyze large-scale data to identify fraud and abuse signals.
• Rapidly identify actionable insights and analyze fraud patterns.
• Develop monitoring frameworks and mitigation solutions for emerging fraud threats.
• Evaluate AI review agent case summaries and improve workflows based on findings.
• Collaborate with the Machine Learning team to recommend model features.
• Participate in design and code reviews, mentoring junior analysts.

Skills

Fraud analytics

SQL

Python

Data science concepts

Communication

Decisioning systems

Education

Bachelor's in quantitative field

Tools

Pandas

NumPy

scikit-learn

Job description

For our client, we are seeking a Senior Analyst, Fraud Intelligence to join the team of a leader in the Information Technology space.

This role will focus on uncovering fraud and abuse patterns across large-scale data environments and turning those findings into practical mitigation strategies. You will partner closely with machine learning, operations, and cross-functional stakeholders to strengthen decisioning workflows and improve risk controls. The position blends hands-on data analysis with strategic input on model features, monitoring frameworks, and review processes. It is a strong fit for a data-driven analyst who can translate complex signals into clear actions that protect the business.

Location: Remote

Compensation: $125,000 – $145,000 annually

Responsibilities

• Analyze large-scale data to identify fraud and abuse signals
• Rapidly identify actionable insights and analyze fraud patterns
• Develop monitoring frameworks and mitigation solutions for emerging fraud threats
• Evaluate AI review agent case summaries and improve workflows based on findings
• Collaborate with the Machine Learning team to recommend model features
• Participate in design and code reviews, mentoring junior analysts

Qualifications

• 3+ years of experience in fraud analytics, preferably in e-commerce or retail
• Bachelor's degree in a quantitative field such as Mathematics, Statistics, or Computer Science
• Strong understanding of data science concepts, including statistical analysis and modeling
• Proficiency in SQL and experience with Python libraries such as pandas, NumPy, and scikit-learn
• Exceptional communication skills with a proven ability to influence cross-functional teams
• Experience with automated decisioning systems is a plus
• High attention to detail and strong intellectual curiosity

Benefits

• Collaborative and supportive team environment
• Full medical, dental, and vision benefits
• Stock options in a rapidly growing startup
• Generous and flexible paid time off policy
• 401(k) plan with financial guidance from Morgan Stanley

Our client is an equal opportunity employer. We encourage you to apply even if you don’t meet every qualification—your background could be exactly what this team needs.