BNY Wealth Management is seeking a Vice President, Data Management & Quantitative Analysis I to help successful individuals and their families build, manage, and sustain their wealth across generations and market cycles by providing analytical project management support and conducting complex data analyses.
Requirements
- Uses technology tools to conduct analyses. Applies data wrangling techniques utilizing SQL, Python (Pandas), and/or other tools to extract and transform data to create actionable insights.
- Applies techniques such as SQL and querying and macro development to extract data for populating models.
- As an advanced user, may do some light programming or system configuration in order set up sophisticated models or algorithms.
- Advanced degree in quantitative analysis preferred.
- 5-7 years experience preferred.
- Experience in quantitative finance and technology preferred.
Responsibilities
- Independently works with internal and client reference data and participates in strategic, complex projects with data support or process automation.
- Master software and internal processes for building and maintaining robotics solutions for operations
- Provides analytical project management support for assigned area.
- With minimal guidance, supports assigned area with advanced, complex data analyses.
- Contributes to the development of the techniques and methodologies to be used for each type of activity/analysis.
- Leads data modeling and quantitative analysis projects and serves as resource to less experienced colleagues.
- Uses technology tools to conduct analyses. Applies data wrangling techniques utilizing SQL, Python (Pandas), and/or other tools to extract and transform data to create actionable insights.
Other
- Bachelors degree or the equivalent combination of education and experience.
- Provides guidance and training to more junior analysts.
- Primarily responsible for the accuracy and quality of own work and the work of assigned project team members.
- Translates complex technical concepts and analyses to non-technical audiences.
- Reviews accuracy of tasks, reports and calculations performed by less experienced colleagues.
