BNY is seeking a SVP Data Management to oversee the development of statistical, financial, and/or econometric models for analyzing asset performance, client reference data, securities data, derivative pricing, risk exposure, or other sophisticated concepts, to drive transformative solutions that redefine industries and uplift communities worldwide.
Requirements
- Experience in quantitative finance and technology preferred.
- Advanced degree in quantitative analysis preferred.
- SQL, querying, and macro development
- Ability to apply techniques such as SQL, querying, and macro development to extract data for populating models and presenting to management.
- Ability to program system configuration to set up sophisticated models or algorithms
- Ability to demonstrate deep understanding of relevant products in assigned area and which analyses, methodologies, and approaches best support assessment of performance, risk, or valuation.
- Ability to use technology applications to conduct complex analyses
Responsibilities
- Oversee the development of statistical, financial, and/or econometric models for analyzing asset performance, client reference data, securities data, derivative pricing, risk exposure, or other sophisticated concepts.
- Provide analytical and project leadership for assigned area, performing advanced, complex statistical and quantitative analyses.
- Collaborate and recommend to management techniques and methodologies to be used for each type of activity/analysis.
- Lead data modeling and quantitative analysis projects, serving as a resource to less experienced colleagues.
- Use technology applications to conduct complex analyses, applying techniques such as SQL, querying, and macro development to extract data for populating models and presenting to management.
- Program system configuration to set up sophisticated models or algorithms and partner with management to evaluate and select the most appropriate technologies.
- Demonstrate deep understanding of relevant products in assigned area and which analyses, methodologies, and approaches best support assessment of performance, risk, or valuation.
Other
- Bachelor’s degree or the equivalent combination of education and experience.
- 10+ years total work experience preferred.
- No formal supervisory responsibility but experience providing work oversight and mentorship to less experienced colleagues is desirable.
- Ability to translate complex technical concepts and analyses to non-technical audiences.
- Ability to provide work oversight to less experienced analysts and input into their performance assessments.
