AmeriSave Mortgage Corp.-posted 3 months ago
$130,000 - $200,000/Yr
Full-time • Mid Level
501-1,000 employees

AmeriSave Mortgage is a leading direct mortgage lender committed to transforming the home financing experience through data-driven decision-making and operational excellence. We are expanding our analytics leadership to further optimize our credit funnel and operational workflows. We are seeking a strategic and technically strong Quantitative Analytics Manager to drive significant efficiency and profitability improvements across our core mortgage operations funnel, which includes Loan Processing, Underwriting (UW), and closing. This role is instrumental in leveraging advanced analytics, statistical methods, and optimization techniques to diagnose bottlenecks, quantify opportunities, and implement data-driven strategies that reduce turn times, lower costs, and enhance operational velocity.

  • Design and execute analyses to inform the logic for dynamically classifying loan files based on projected profitability, complexity, and risk.
  • Develop routing algorithms to move loan files to the optimal fulfillment channels and teams.
  • Conduct deep-dive root cause analysis on operational data to identify and quantify bottlenecks.
  • Model the impact of potential process changes or technology integrations to significantly reduce cycle times.
  • Quantitatively evaluate and prove out the ROI of new automation tools and technology integrations.
  • Utilize data science techniques to design and analytically validate alternative Underwriting workflows and decision matrices.
  • Design and implement robust testing methodologies and performance measurement dashboards to track the realized impact of implemented changes on key operational KPIs.
  • Bachelor’s or master’s degree in Statistics, Mathematics, Data Science, Economics, or related field.
  • 8+ years of experience in quantitative analytics, with at least 3 years in a leadership role.
  • Deep understanding of credit lifecycle, operational workflows, and funnel analytics.
  • Strong proficiency in SQL, Python, R, or similar tools.
  • Experience with credit data analysis.
  • Proven ability to lead cross-functional initiatives and communicate with executive stakeholders.
  • Experience in mortgage, lending, or financial services.
  • Familiarity with CRM, LOS, and workflow automation platforms and tools such as Truv, Work number, Tax Guard etc.
  • Exposure to credit scoring models and regulatory analytics.
  • 401(k)
  • Dental insurance
  • Disability insurance
  • Employee discounts
  • Health insurance
  • Life insurance
  • Paid time off
  • 12 paid holidays per year
  • Paid training
  • Referral program
  • Vision insurance
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