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VP/Director, Quantitative Trading Strategist - US Credit Desk, New York, New York

Created 07/21/2021
Reference 21043245
Category Investment Banking
Job type Full Time
Country United States
State New York
City New York
Zip 10001
Salary Competitive
Job Description:

The US Credit Trading Franchise is seeking a Quantitative Trading Strategist to join the team in New York. The team is responsible for the research and development of quantitative trading strategies to inform and enhance the trading decisions of the US Credit Flow Desk. The successful candidate will sit directly on the US Credit Flow trading desk, and co-report into the trading and quant organizations. The primary focus will be on developing systematic and algorithmic trading strategies while optimizing work-flow to enhance trading & risk management decisions.

The role will require you to navigate existing data sets, source novel data sets, and identify relationships in these data to produce or improve systematic and algorithmic trading strategies.

You should be comfortable managing a project from start through to production.

Responsibilities include:
  • Analyzing large (and small) data sets to extract signal from noise, informing both automated and semi-automated trading strategies.
  • Researching systematic alpha signals to be used across our credit flow business, with a focus on algorithmic and portfolio trading.
  • Utilizing optimization techniques to inform trading decisions across desk strategies.
  • Optimization of methods / algorithms to price and hedge corporate bonds.
  • Develop US Credit ETF creation/redemption optimization tools to inform ETF trading decisions.
  • Partnering with Quant Research and Technology to develop and maintain tools which inform trading decisions.

Requirements
  • Academic background at undergraduate or Masters/PhD level in a quantitative subject (Physics, Engineering, Statistics, Mathematics, Computer Science or other analytical background).
  • Experience with optimization tools and methods (cvxpy, cvxopt, commercial solvers) and portfolio optimization methods is a plus.
  • Proven ability to deliver ideas into a production.
  • Understanding of data analysis & modeling techniques (statistics, machine learning, signal processing).
  • Proficient programming skills in at least one data analysis language (Python/R/Matlab) and one production language (Java, C++, C#). Experience in other languages is also welcome, though you will be required to learn our internal stack.

Good to Have, Not Required
  • Previous experience of financial markets, credit electronic trading advantageous
  • Experience in electronic / algorithmic market making
  • Experience in statistical arbitrage techniques


Job Band:
H5

Shift:
1st shift (United States of America)

Hours Per Week:
40

Weekly Schedule:

Referral Bonus Amount:
0
--> Job Description:

The US Credit Trading Franchise is seeking a Quantitative Trading Strategist to join the team in New York. The team is responsible for the research and development of quantitative trading strategies to inform and enhance the trading decisions of the US Credit Flow Desk. The successful candidate will sit directly on the US Credit Flow trading desk, and co-report into the trading and quant organizations. The primary focus will be on developing systematic and algorithmic trading strategies while optimizing work-flow to enhance trading & risk management decisions.

The role will require you to navigate existing data sets, source novel data sets, and identify relationships in these data to produce or improve systematic and algorithmic trading strategies.

You should be comfortable managing a project from start through to production.

Responsibilities include:
  • Analyzing large (and small) data sets to extract signal from noise, informing both automated and semi-automated trading strategies.
  • Researching systematic alpha signals to be used across our credit flow business, with a focus on algorithmic and portfolio trading.
  • Utilizing optimization techniques to inform trading decisions across desk strategies.
  • Optimization of methods / algorithms to price and hedge corporate bonds.
  • Develop US Credit ETF creation/redemption optimization tools to inform ETF trading decisions.
  • Partnering with Quant Research and Technology to develop and maintain tools which inform trading decisions.

Requirements
  • Academic background at undergraduate or Masters/PhD level in a quantitative subject (Physics, Engineering, Statistics, Mathematics, Computer Science or other analytical background).
  • Experience with optimization tools and methods (cvxpy, cvxopt, commercial solvers) and portfolio optimization methods is a plus.
  • Proven ability to deliver ideas into a production.
  • Understanding of data analysis & modeling techniques (statistics, machine learning, signal processing).
  • Proficient programming skills in at least one data analysis language (Python/R/Matlab) and one production language (Java, C++, C#). Experience in other languages is also welcome, though you will be required to learn our internal stack.

Good to Have, Not Required
  • Previous experience of financial markets, credit electronic trading advantageous
  • Experience in electronic / algorithmic market making
  • Experience in statistical arbitrage techniques


Job Band:
H5

Shift:
1st shift (United States of America)

Hours Per Week:
40

Weekly Schedule:

Referral Bonus Amount:
0
Job Description:

The US Credit Trading Franchise is seeking a Quantitative Trading Strategist to join the team in New York. The team is responsible for the research and development of quantitative trading strategies to inform and enhance the trading decisions of the US Credit Flow Desk. The successful candidate will sit directly on the US Credit Flow trading desk, and co-report into the trading and quant organizations. The primary focus will be on developing systematic and algorithmic trading strategies while optimizing work-flow to enhance trading & risk management decisions.

The role will require you to navigate existing data sets, source novel data sets, and identify relationships in these data to produce or improve systematic and algorithmic trading strategies.

You should be comfortable managing a project from start through to production.

Responsibilities include:
  • Analyzing large (and small) data sets to extract signal from noise, informing both automated and semi-automated trading strategies.
  • Researching systematic alpha signals to be used across our credit flow business, with a focus on algorithmic and portfolio trading.
  • Utilizing optimization techniques to inform trading decisions across desk strategies.
  • Optimization of methods / algorithms to price and hedge corporate bonds.
  • Develop US Credit ETF creation/redemption optimization tools to inform ETF trading decisions.
  • Partnering with Quant Research and Technology to develop and maintain tools which inform trading decisions.

Requirements
  • Academic background at undergraduate or Masters/PhD level in a quantitative subject (Physics, Engineering, Statistics, Mathematics, Computer Science or other analytical background).
  • Experience with optimization tools and methods (cvxpy, cvxopt, commercial solvers) and portfolio optimization methods is a plus.
  • Proven ability to deliver ideas into a production.
  • Understanding of data analysis & modeling techniques (statistics, machine learning, signal processing).
  • Proficient programming skills in at least one data analysis language (Python/R/Matlab) and one production language (Java, C++, C#). Experience in other languages is also welcome, though you will be required to learn our internal stack.

Good to Have, Not Required
  • Previous experience of financial markets, credit electronic trading advantageous
  • Experience in electronic / algorithmic market making
  • Experience in statistical arbitrage techniques


Shift:
1st shift (United States of America)

Hours Per Week:
40
Learn more about this role
Employer Bank of America

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