
at J.P. Morgan
Bulge Bracket Investment BanksPosted 5 days ago
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**Senior Associate in Home Lending Modeling & Strategic Forecast** leads advanced forecasting models, guiding strategic decisions and ensuring regulatory compliance. Responsibilities include developing and refining quantitative models, leading enhancements, and interacing with stakeholders. This role requires a Master's degree in a quantitative field, 5+ years of relevant experience, proficiency in Python and SQL, and strong analytical and communication skills. Successful candidates will leverage their experience to drive process improvements and deploy new technologies, with a preference given to those with a PhD, CFA/FRM certification, or AI/ML experience.
- Compensation
- Not specified
- City
- Not specified
- Country
- United States
Currency: Not specified
Full Job Description
Location: OH, United States
Join our team to lead the development and enhancement of advanced forecasting models for Home Lending Finance, driving strategic decisions and regulatory compliance through high-quality analytics and cross-functional collaboration.
As a Senior Associate in Home Lending Planning and Analysis (P&A), you will lead the development and enhancement of advanced forecasting models that drive strategic decision-making and regulatory compliance. Youll collaborate with cross-functional teams to deliver high-quality analytics and implement innovative technologies. This role offers significant opportunities for professional growth and impactful contributions to the organizations financial and operational objectives.
Job responsibilities
Develop, refine, and maintain qualitative and quantitative models, including time series forecasting, econometric, and machine learning models, in alignment with firms model risk guidelines and regulatory requirements.
Lead statistical model enhancements and perform in-depth analysis, including evaluation of look-back time frames, alternative methodologies, and optimization of model assumptions.
Assist with issue resolution for model-related challenges, ensuring timely identification, escalation, and closure of issues. Prepare and maintain model documentation for regulatory submissions and senior management reports, ensuring accuracy, completeness, and compliance.
Support model assumptions and methodologies in technical documentation and during discussions with Model Risk Governance and Review and other stakeholders.
Interface with multiple stakeholders, including Home Lending leadership, business finance, technology, risk to communicate findings, resolve issues, and drive process improvements.
Conduct business and process due diligence to develop functional requirement documents and support user acceptance testing (UAT), including test planning, execution, and training documentation.
Evaluate, introduce, and deploy new tools and technologies to the Home Lending team, developing use cases and leading technology transformation initiatives.
Required qualifications, capabilities, and skills
Masters degree required in Finance, Accounting, Economics, Analytics, Engineering, Mathematics, Statistics, or a related quantitative field.
5+ years of experience in finance, management consulting, analytics, risk, or financial planning & analysis roles.
Advanced quantitative, analytical, and problem-solving skills, with hands-on experience in econometric modeling (e.g., OLS, time series) and familiarity with machine learning techniques.
Proficiency in Python (required), SQL, and strong knowledge of Microsoft Office.
Experience with analytical and database platforms such as Essbase, Tableau, Alteryx, and Databricks.
Project management experience, with the ability to manage multiple tasks and deliverables simultaneously.
Excellent written and verbal communication skills, with the ability to create clear and concise documentation and communicate effectively with stakeholders at all levels, including governance forums.
Preferred qualifications, capabilities, and skills
- PhD degree preferred in a quantitative field.
- CFA/FRM certification a plus.
- Experience in mortgage banking, regulatory reporting, and model risk management.
- Data science, AI/ML, and automation experience.
- Understanding of macroeconomic and business environments.
