Quantitative Developer

NYC - hybrid 3 days onsite/week

10 months, possible extension/conversion

FRTB Market Quantitative Analyst

Must-have skill sets

1. Strong python programming skills. Development experience in large scale production systems, not just offline analytical code on their own PC. Have experience committing code into production. – Interview will be programming intensive; anyone less than that has no chance.

2. Extensive experience in handling large amount of data. Knowing SQL inside out.

3. Quick learner. The person needs to pick up market risk knowledge and asset class knowledge at the job. Has to be open to training and expects lots of learning.

Not looking for:

1. Project managers / program managers

2. Risk managers

The front office Market Quantitative Analysis (MQA) is looking for a quantitative analyst in the In-Business Market Risk MQA team, working along with trading and in-business risk managers in managing market risk metrics and capital.

Responsibilities:

Some key responsibilities include:
• Build advanced analytical tools and applications including AI powered apps, for the business and traders’ use to assess market risk, stress loss and capital metrics, and to develop efficient portfolio level hedge strategies.
• Develop well-structured high-quality code and contribute to contribute to large-scale in-house python libraries.
• Perform in-depth diagnosis of the current market risk and capital models and processes, partner with the business and other quant teams to propose and drive enhancement.
• Partner with traders, provide cost-benefit analysis to help on business prioritization, guidance and direction.

Qualifications:
• 6+ years of experience in quantitative modeling in the financial industry.
• Must have strong technical/programming skills in python. Experience in collaborative code development through use of Git/Bitbucket and similar platforms. Familiar with software development principles. Able to design, structure, and modularize complicated program.
• Familiar with SQL, and experience working with large dataset. Skilled in data cleaning, transformation, and processing using Python libraries such as pandas and numpy.
• Proficiency in delivering solutions using front-end frameworks like Angular and visualization tools like Tableau is a plus.
• Understanding of commonly used market risk metrics and method such as VaR, stress testing is a plus.
• Clear and concise written and verbal communication skills.

Education:
• A PhD or Master’s degree in a technical discipline such as statistics, mathematics, physics, computer science, quantitative finance, operations research or similar.