Remote Quantitative Analytics Lending Analyst

Role

Quantitative Analytics Lending Analyst

Remote (Must leave near: Greenwich, CT, Plano, TX, Indianapolis, IN, Jacksonville, FL, Nashville, TN, or Orange CA)

Full Time, Direct Hire

$100-150k base + bonus

US Citizen, GC Holders or Authorized to Work in US

If interested, please contact Margot Parsons at  or call

• The Quantitative Analytics Lending Analyst will be responsible for helping to reshape and elevate the company's residential mortgage lending data analysis, including marketing and customer engagement to pricing analytics, P&L, and market-trend insights, while modernizing the company's analytics toolkit.
• Leverage and bridge the company's investor-grade analytics platform with our lending affiliate: adapting the company's proprietary models and tools for lending use cases, integrating lending performance back into the company's ecosystem, and driving actionable insights for capital-markets and investor initiatives.

• End-to-end data ownership: Clean, reorganize, and harmonize loan-origination, servicing, marketing, and customer datasets to extract actionable signals and performance metrics.
• Tool & model adaptation: Write wrappers and interfaces to deploy existing pricing, prepayment, and credit-risk models within the lending platform.
• Analytics integration: Feed lending performance and P&L results back into company analytics ecosystem to close the loop and inform investor reporting.
• Reporting & dashboards: Develop and maintain self-service dashboards and reports to track key lending metrics - recapture rates, marketing ROI, pricing variance, P&L attribution, and market trends.
• Performance reporting: Prepare, present, and explain performance reports to senior lending management; gather and analyze feedback from loan officers to refine analytics and strategies.
• Strategic partnerships: Collaborate with pricing, portfolio, investor-relations, and capital-markets teams to translate analytics into lending strategies and execute investor-driven initiatives.
• Ecosystem modernization: Automate data pipelines, standardize definitions across CCM and lending systems, and deploy scalable analytics tools.
• Cross-functional liaison: Work with IT, CRM, operations, and third-party vendors to ensure data quality and timely delivery of insights.
• Ad-hoc analysis: Respond rapidly to one-off requests from senior management, investors, and affiliated divisions.
• Perform other duties and projects as assigned.

• Bachelor's or advanced degree in a quantitative field (e.g., Mathematics, Statistics, Computer Science, Engineering, Finance).
• A minimum of one year of hands-on experience in mortgage-lending analytics, capital-markets analytics, or a related role; exceptional analysts with strong programming skills will also be considered.
• Strong Python and SQL skills for data extraction, transformation, and analysis; familiarity with machine-learning techniques is highly desirable.
• Proven ability to adapt and deploy proprietary quantitative models—experience writing wrappers or APIs to integrate analytics pipelines.
• Demonstrated aptitude for working with and organizing unstructured or messy marketing/customer data: data-cleaning, ETL, and signal-extraction expertise required.
• Experience building self-service dashboards or reporting tools (e.g., Tableau or similar).
• Solid working knowledge of loan-origination and servicing workflows, including mechanisms for recapturing existing customers.
• Excellent communication skills: able to translate complex analytics into clear, actionable insights for non-technical stakeholders.
• Highly organized, self-motivated, and adept at juggling multiple high-priority projects in a fast-paced environment
• Excellent skills in mathematics and statistics.
• Hands-on experience using Python and various statistical packages to process and analyze large data sets.
• Ability to apply popular machine learning techniques with reasonable understanding of their underlying algorithms.
• Experience with Linux environments is preferred.
• Highly motivated, team-oriented, a quick learner with good communication skills.
• Strong organizational skills and time management skills to perform multiple tasks within limited time frames.

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