Apply Now<br><br>Remote or Hybrid at Glen Mills, PA / Tempe, AZ / Coppell, TX<br><br>At Flagship Financial Group, we strive to make a positive impact on our customers' lives through responsible auto financing and our employees' careers through continuous learning and advancement opportunities. Backed by new ownership and a substantial, ongoing investment in technology, data, and analytics, we are expanding our quantitative capabilities to support the next phase of our growth.<br><br><strong>We are seeking a Senior Quantitative Analyst </strong>to develop, maintain, and enhance the credit and risk models behind our auto lending originations, including credit decisioning, loss forecasting, and pricing. You will join an established team of senior quantitative analysts, own the originations modeling suite, and partner closely with Credit, Risk, and Technology to turn analytical work into decisions that move the business.<br><br>Key Responsibilities<br><br><ul><li> Develop, maintain, and enhance originations models, including application scoring, probability of default (PD) frameworks, loss timing curves (LTC), and pricing models.</li><li> Analyze credit attributes, application data, and portfolio performance data to identify risk drivers, support segmentation strategies, and improve model calibration.</li><li> Work directly with raw credit bureau data — parsing bureau files, interpreting tradeline-level detail, and constructing and validating custom credit attributes for use in modeling.</li><li> Evaluate alternative data sources and portfolio analytics to support model development and ongoing performance improvement.</li><li> Validate and monitor model performance against actual outcomes and contribute to structured recalibration and model refresh cycles.</li><li> Identify model performance issues and opportunities for enhancement, recommending and implementing improvements as appropriate.</li><li> Maintain comprehensive documentation throughout the model lifecycle — design, development, testing, validation, and monitoring — consistent with model risk management standards and sufficient to support independent validation, audit, and regulatory review.</li><li> Serve as a subject matter expert on originations modeling and provide analytical insights to support business decisions.</li><li> Mentor junior analysts and contribute to the technical growth and development of the broader Quantitative Analysis team.</li><li> Collaborate cross-functionally with Credit, Risk, Operations, Technology, and other stakeholders to drive data-informed decision-making.</li><li> Perform other duties as required or assigned.<br><br></li></ul>Who You Are<br><br><strong>The Quantitative Problem Solver: </strong>You use data, analytics, and statistical modeling to solve complex business problems. You enjoy uncovering patterns in large data sets, and you can translate what you find into recommendations that balance risk and growth.<br><br><strong>The Collaborative Partner: </strong>You explain complex quantitative concepts clearly and practically, and you work effectively with both technical and non-technical stakeholders across the organization.<br><br><strong>The Technical Expert: </strong>You hold high standards for model integrity, documentation, and governance, and you continuously look for ways to improve analytical processes and methodologies.<br><br><strong>Qualifications<br><br></strong><strong>Experience:<br><br></strong><ul><li> 4–7 years of hands-on experience in quantitative model development. Candidates with 7+ years of experience and/or advanced education may be considered for an Advanced Senior level role.<br><br></li></ul><strong>Industry Context<br><br></strong><ul><li> Experience in auto finance, consumer lending, credit risk modeling, or related financial services environments preferred.<br><br></li></ul><strong>Technical Skills<br><br></strong><ul><li> Strong proficiency in Python or R.<br><br></li></ul><strong>Bureau Data<br><br></strong><ul><li> Hands-on familiarity with credit bureau data is strongly preferred, including experience parsing bureau files and working with tradeline-level data to build and test credit attributes.<br><br></li></ul><strong>Education<br><br></strong><ul><li> Bachelor's degree in Statistics, Mathematics, Engineering, Finance, Economics, Data Science, or a related field required.</li><li> Master’s degree or PhD preferred for advanced-level candidates.<br><br></li></ul><strong>Skills & Abilities<br><br></strong><ul><li> Strong knowledge of statistical techniques, predictive modeling, machine learning methodologies, and model validation practices.</li><li> Familiarity with model risk governance and regulatory expectations for model development, validation, and documentation in a lending environment.</li><li> Experience working with large data sets and translating complex analyses into business-driven recommendations.</li><li> Proven ability to manage multiple priorities and deliver high-quality work in a fast-paced environment.</li><li> Exceptional analytical, organizational, problem-solving, and communication skills.<br><br></li></ul><strong>Compensation<br><br></strong>Base Salary Range: $105,000 – $155,000 annually. This range spans both the Senior and Advanced Senior levels; an individual offer will fall within the portion of the range applicable to the level for which a candidate is hired, and will reflect experience, education, and work location.<br><br>Additional Compensation: This position is eligible for an annual incentive bonus and a full benefits package.<br><br>Location & Work Schedule<br><br><strong>Location: </strong>Remote opportunity or hybrid at our Glen Mills, PA, Tempe, AZ, or Coppell, TX locations.<br><br><strong>Schedule: </strong>Full-time position with standard business hours; additional flexibility may be required based on business needs.<br><br>Why Join Us?<br><br>This is an opportunity to join a company with a strong, established book of business that is investing seriously in technology, analytics, and modeling capability. You will have real influence over the models that drive credit decisions, room to modernize how the work gets done, and talented colleagues to do it with. The models you build here will be used — not shelved.