Quantitative Analytics Lending REMOTE

At CGS Business Solutions, we’re dedicated to helping skilled IT and business professionals take the next meaningful step in their careers. Whether you're exploring project-based consulting roles or seeking a long-term position, we connect you with opportunities that align with your expertise, your goals, and your growth trajectory.

Backed by deep industry insight and our proven Talent Flow™ Framework, we ensure every role we present is thoughtfully matched to your skills, passions, and career ambitions. If you're ready for a role that challenges you and moves your career forward, we’re currently partnering with leading organizations to fill the following opportunity:

Our nationwide Financial Services customer is seeking a Quantitative Analytics Lending Analyst to work “REMOTE and being 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.

What you'll do:

• 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 within the lending platform.
• Analytics integration: Feed lending performance and P&L results back into CCM’s 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.

What you'll need:

• 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.
• Strong SQL and Python skills for data extraction and analysis.
• Experience with Linux environments is…