Finding the best job has never been easier
Bank Of America VP/Director Mortgage Quant Strat United States, New York, New York 448244452
Share
Job Description:
Job Description:
This job is responsible for conducting quantitative analytics and complex modeling projects for specific business units or risk types. Key responsibilities include leading the development of new models, analytic processes, or system approaches, creating technical documentation for related activities, and working with Technology staff in the design of systems to run models developed. Job expectations may include the ability to influence strategic direction, as well as develop tactical plans.
The Mortgage Quantitative Strats Group (QSG) is looking for a new hire to support expanded deliverables from the Mortgage trading desk. QSG is central to a number of complex, business critical deliveries including regulatory programs such as IBOR Transition, FRTB, and CCAR, internal transformational and operational excellence programs, and desk facing projects in areas such as electronic trading, and collateral modelling. This role is in a dynamic front office environment, combining daily challenges with longer term projects, collaborating with research, external clients, trading, and technology and market risk. Excellent communication skills, both verbal and written, are required and ability to work in fast paced environment. The person taking on this role will be a self-starter, capable of working independently with minimal supervision.
Responsibilities:
- Global Quantitative team providing solutions across regions of business and asset classes.
- The role is a front office business focused role, and involves working with mortgage research and trading partners on a daily basis.
- The candidate will work on a very wide range of projects including data analytics, statistical and machine learning based modelling, e-trading and hedging projects with the trading desk.
- The role involves hands on programming experience in SQL and Python.
- Working entirely in Front Office alongside mortgage quant colleagues & trading specialists.
- Support mortgage traders, research strategies and operational trading tools.
- Performs end-to-end market risk stress testing including scenario design, scenario implementation, results consolidation, internal and external reporting, and analyzes stress scenario results to better understand key drivers
- Leads the planning related to setting quantitative work priorities in line with the bank’s overall strategy and prioritization
- Identifies continuous improvements through reviews of approval decisions on relevant model development or model validation tasks, critical feedback on technical documentation, and effective challenges on model development/validation
- Maintains and provides oversight of model development and model risk management in respective focus areas to support business requirements and the enterprise's risk appetite
- Leads and provides methodological, analytical, and technical guidance to effectively challenge and influence the strategic direction and tactical approaches of development/validation projects and identify areas of potential risk
- Works closely with model stakeholders and senior management with regard to communication of submission and validation outcomes
- Performs statistical analysis on large datasets and interprets results using both qualitative and quantitative approaches
Skills:
- Quantitative Development
- Data Modeling
- Data and Trend Analysis
- Masters or PhD or equivalent level preferred
- Proven experience within a relevant quant/finance field.
- Excellent programming skills in python, sql and C++ preferred.
- Mortgage experience preferred, good business and modeling knowledge across asset classes.
- Prior experience working in front office is preferable.
- Ability to multitask and work independently given complex tasks.
- Excellent communication skills.
- Excellent mathematical skills.
Master’s degree in related field or equivalent work experience
1st shift (United States of America)These jobs might be a good fit
