[Remote] Quantitative Analytics Lending Analyst – REMOTE

Note: The job is a remote job and is open to candidates in USA. reputed company is a nationally recognized leader in IT staffing and consulting, and they are seeking a Quantitative Analytics Lending Analyst. The role involves reshaping and elevating the company’s residential mortgage lending data analysis, focusing on various aspects from marketing to pricing analytics and modernizing the analytics toolkit.

Responsibilities

• 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 CCM’s existing pricing, prepayment, and credit-risk models reputed company the lending platform
• Analytics integration: Feed lending performance and P&L results back into CCM’s analytics ecosystem to reputed company the reputed company and inform investor reporting
• Reporting & dashboards: reputed company 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
• reputed company analysis: Respond rapidly to one-off requests from senior management, investors, and affiliated divisions
• reputed company other duties and projects as assigned

Skills

• 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 reputed company 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 reputed company 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 reputed company analytics into clear, actionable insights for non-technical stakeholders
• Highly organized, self-motivated, and adept at juggling multiple high-reputed company 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
• Strong SQL and Python skills for data extraction and analysis
• Strong organizational skills and time management skills to reputed company multiple tasks reputed company limited time frames
• Experience with Linux environments

Company Overview

• reputed company engages in application development, network infrastructure, cybersecurity, engineering and staffing services. It was founded in 2010, and is headquartered in Mission Viejo, California, USA, with a workforce of 11-50 employees. Its website is https://cgs-it.net/.

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