Equity Volatility Quantitative Researcher

Equity Volatility Quantitative Researcher

LondonNew York

Posted 123 Days Ago

With respect to NY, CA, and IL based applicants, the starting base pay range for this role is between USD 175000 and USD 250000 annually. The actual base pay is dependent upon several factors, including, but not limited to, relevant experience, business needs and market demands. This role may also be eligible for bonus compensation and employee benefits.

Balyasny Asset Management L.P. (BAM) founded in 2001, is an institutional investment firm dedicated to delivering consistent, uncorrelated absolute returns in all market environments. BAM has offices in Chicago, New York, Greenwich, San Francisco, Hong Kong and London.

At BAM, we are our talent. We are a growing firm that offers a multitude of professional opportunities. Through BAM’s selective hiring process, we target the best and brightest in the business, and strive to create an environment which attracts and retains top talent. Maintaining a culture where people are energized to come to work is paramount to our success. Our team is motivated to perform each and every day.

As a result, BAM has built a reputation as a firm that provides the tools necessary for talented individuals to achieve their goals and reach their highest potential.

ROLE OVERVIEW:

BAM is seeking an experienced Quantitative Researcher with expertise in building, supporting and integrating globally accessible quant trading infrastructure. The candidate will interact with portfolio managers and quant researchers to building requisite toolkits. The optimal candidate will have prior experience at a financial services organization with an exceptional technical background and in-depth knowledge of quantitative trading systems including back testing, simulation, performance testing and market data. This person will need to be a strong communicator, able to multi-task and have the ability to excel in a fast-paced trading environment.

KEY RESPONSIBILITIES

• Support portfolio manager and analysts in building out bespoke alpha research tools using in-house analytics

• Assist in the buildout of the internal analytics for D1 and Equity Derivative products

• Work closely with the investment team and build valuation tools and screeners to improve their trading and filtration process

• Test various trading strategies, perform adhoc research and deliver the results via Excel/Python framework

• Support trading and risk management with scenario analysis, relative value, and basis trading analytics.

• Work closely with business users and platform developers to capture requirements and handle onboarding and integration of vendor models and datasets

• Document model assumptions, code architecture, and user-facing APIs

• Perform with minimum supervision and exercise sound judgment

• Help identify and automate manual processes

• Unit-test, benchmark, and profile code for performance and numerical stability

REQUIRED QUALIFICATIONS

• Master degree/PhD in a technical area, such as Math, Physics, Statistics, Engineering, Computational Finance or other quantitative discipline preferred

• Programming experience in Python, with the ability to test ideas and develop infrastructure for further research. C++ is desirable

• Understanding of listed and OTC markets for D1 and equities options as well as volatility index. Experience in local and/or stochastic vol models implementation is desirable

• Knowledge of statistics, including time series analysis and regressions

• Experience building trading tools is desirable.

• Experience in alpha research and signal generation is desirable 

THE IDEAL CANDIDATE WILL BE SOMEONE WHO DEMONSTRATES 

• Strong desire to work collaboratively with the team

• Problem solving skills and ability to identify and implement appropriate solutions

• Ability to prioritize and manage multiple tasks and projects concurrently to meet/exceed deadline

• Documentation skills – ability to represent ideas, requirements, and problems in clear and concise documents

• Outstanding attention to detail and strong organization skills