The position is for a Quantitative Analyst within Truist’s Financial Management Quantitative Analytics department.
Financial Management Quantitative Analytics is responsible for the development and documentation of models supporting capital stress testing, asset and liability management, NII forecasting, EVE, and other corporate initiatives.
The incumbent serves as a contributor supporting end-to-end execution of analytics projects, including model development, documentation and deployment.
Quantitative analytics projects support Corporate Treasury’s objective to model the behavior of Truist’s balance sheet and income statement in support of capital stress testing, allowance for loan and lease losses, balance sheet manage, and other corporate initiatives.
Following is a summary of the essential functions for this job. Other duties may be performed, both major and minor, which are not mentioned below. Specific activities may change from time to time.
1. Develop models and analytics in support of CCAR, internal stress testing, capital planning, NII forecasting, ALM, EVE, and those associated models and qualitative methodologies.
2. Contribute to a positive and highly engaged team by championing a positive working environment through relationship development with peers, direct reports, and leadership – proactively seek guidance, clarification, and feedback
3. Apply with limited support documentation, development, and implementation standards and procedures.
4. Utilizing limited instruction, exhibit the ability absorb direction and develop and implement quantitative models consistent with management expectations.
5. With support address model validation recommendations and remediate issues.
6. Utilize quantitative techniques to measure and analyze model risks and form opinions on the strengths and limitations of the respective models.
7. Build, monitor, and review existing models. This includes conducting ongoing communication with model owners and model developers during the course of the entire model development and model review process.
8. Facilitate user and management understanding and acceptance of proposed models by preparing high quality documentation, including presentations, explaining the model and its validity for its intended use. Provide support during verbal presentations to stakeholders and oversight groups.
9. For deployed models, develop and execute ongoing model verification, performance reporting, and assist with change management processes and procedures, including but not limited to, back testing, including outcomes analysis. Work with model users and stakeholders to ensure models are fulfilling the objectives set for them.
10. Ensure that models comply with BB&T requirements for model development, documentation, ongoing verification, coding standards, change management and other policy requirements; address model validation recommendations and remediate issues.
The requirements listed below are representative of the knowledge, skill and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
1. 2+ years’ experience in financial services industry with focus on model development and quantitative analytics – PhD in a quantitative discipline may substitute for experience expectations
2. Master’s degree in Statistics, Econometrics, Actuarial Science, Applied Mathematics, Operations Research, or other applied quantitative science, or equivalent education and related training
3. Demonstrated experience performing advanced quantitative analysis and developing econometric models
4. Practice analyzing and manipulating large and complex data to identify data integrity issues and researching industry practices related to model methodologies.
5. Contribute to a positive and highly engaged team
1. PhD in a quantitative discipline preferred
2. Demonstrated execution within of quantitative model development standards, procedures, and practice
3. Strong verbal, written, and interpersonal skills
4. Proficiency utilizing Microsoft Office tools to prepare and present analysis
5. Experience with skills SAS and SQL (or significant demonstrated experience with alternative quantitative programming languages – R, Matlab, etc.)
6. Excellent analytical and quantitative skills