Senior Quant Analytics Lead – Risk & ML Modeling (Remote)

Ladders; United States; On-site; USD 201,000 - 261,000; Full time

Benefits offered by this job

Medical coverage for employees and/or/

Technology stipends

Generous vacation and holidays

Employee stock purchase plan

Remote-first with office flexibility

Job summary

Ladders is seeking a Senior Manager Quantitative Analytics to lead a team of specialists focused on data, AI-enabled capabilities, and scalable tech in a regulated financial services setting.

You will partner with business, technical, and operational stakeholders to surface trends, build reporting, and translate analysis into action, strengthening data-driven execution across the organization.

Qualifications

• 9+ years in a technical role (model development, validation, or quantitative analytics).
• Deep expertise in machine learning, underwriting, and credit risk.
• Advanced Python scripting and SQL skills for data handling.
• Proven experience managing and mentoring quantitative teams.
• BS, MS, or PhD in a quantitative discipline (Statistics, Quantitative Finance, Mathematics, Data Science).
• Analytical problem-solver with attention to detail.
• Excellent communicator able to convey complex concepts effectively.

Responsibilities

• Lead and manage a team of quantitative professionals in the risk sector.
• Validate sophisticated machine learning models for underwriting and credit risk.
• Conduct thorough technical reviews to ensure model accuracy.
• Identify model weaknesses and collaborate on remediation efforts.
• Enhance the enterprise-wide Model Risk Management framework.
• Ensure compliance with internal standards and regulatory requirements.

Skills

Machine learning

Credit risk

Underwriting

Python

SQL

Team leadership

Quantitative analytics

Communication

Education

BS/MS/PhD in Statistics/Quantitative Finance/Mathematics/Data Science

Tools

Python

SQL

Job description

Ladders is seeking a Senior Manager Quantitative Analytics to lead a team of specialists focused on data, AI-enabled capabilities, and scalable tech in a regulated financial services setting.

You will partner with business, technical, and operational stakeholders to surface trends, build reporting, and translate analysis into action, strengthening data-driven execution across the organization.