RBC
Vice President Quantitative Risk, RBC Capital Markets LLC, Jersey City, NJ:
Jersey City, New Jersey, United States of America · Exec · Full-time
Sponsorship not specifiedDetected 28 days ago
PythonSQLGrafanaMachine LearningData ScienceData VisualizationNLPStatisticsResearchCollaborationActuarial Science
About the role
- Validating and monitoring model results.
- Conducting backtesting and performance analysis of trading strategies.
- Maintaining and enhancing existing quantitative research infrastructure.
Responsibilities
- Maintaining a workplace where our employees feel supported to perform at their best, effectively collaborate, drive innovation, and grow professionally helps to bring our Purpose to life and create value for our clients and communities.
- RBC strives to deliver this through policies and programs intended to foster a workplace based on respect, belonging and opportunity for all.
- Expand your limits and create a new future together at RBC.
- Find out how we use our passion and drive to enhance the well-being of our clients and communities at jobs.rbc.com.
Requirements
- Must have a Master's degree in Statistics, Maths, Quantitative Finance, Data Science, Computer Science or a related field and 5 years of related work experience.
- Must have 5 years of experience in:
- Must have 3 years of experience in:
Nice to have
- and paid time-off plan.
Compensation
- Developing quantitative risk metrics.
- Validating and monitoring model results.
- Automating trading and sales process.
- Building trading tools.
- Conducting backtesting and performance analysis of trading strategies.
- Collaborating with traders and sales teams to optimize pricing models.
Benefits
- Building statistical and machine learning models in the space of U.S. credit and municipal bond market.
Company info
- At RBC, we are guided by living shared values of Client First, Integrity, Collaboration, Respect and Excellence and winning together as One RBC.
This listing is sourced directly from RBC's careers page and normalized into a canonical job model.