below marketmost similar roles pay hereabove market
This role pays more than
73%
of similar roles. Most pay
$143,950–$215,000
— the blue band above.
At the midpoint, this role pays about
$212k
versus about
$179k
for comparable roles.
Based on 240 similar postings.
Employer
About Balyasny Asset Management
Balyasny Asset Management (BAM) is a global multi-manager hedge fund offering diversified investment strategies across equities, macro, commodities, and systematic trading.
Balyasny Asset Management currently has
53 open roles
on FindRole.
Listed pay typically runs
$175,000–$250,000
across 37 roles with salary data.
The Equity Volatility Quantitative Researcher will join the team to build, support, and integrate globally accessible quant trading infrastructure. This role involves collaborating with portfolio managers and analysts to develop bespoke alpha research tools, internal analytics for D1 and Equity Derivative products, and valuation screeners. Key responsibilities include testing trading strategies, performing scenario analysis, and handling the onboarding of vendor models and datasets. The candidate must utilize Python and Excel frameworks, with C++ experience being desirable. Required skills include knowledge of statistics, time series analysis, regressions, and an understanding of listed and OTC markets for equities options and volatility indices. The position focuses on solving technical problems related to back testing, simulation, performance testing, and market data while documenting model assumptions and code architecture.
Build bespoke alpha research tools and internal analytics for D1 and Equity Derivative products.
Develop valuation tools and screeners to improve trading and filtration processes.
Test trading strategies and perform ad-hoc research using Excel and Python frameworks.
Provide scenario analysis, relative value, and basis trading analytics for trading and risk management.
Capture requirements and manage the onboarding and integration of vendor models and datasets.
Document model assumptions, code architecture, and user-facing APIs.
Unit-test, benchmark, and profile code for performance and numerical stability.
Identify and automate manual processes to improve operational efficiency.
What we're looking for
Master degree or PhD in a technical area such as Math, Physics, Statistics, Engineering, Computational Finance, or other quantitative discipline (preferred).
Programming experience in Python to test ideas and develop infrastructure for further research.
C++ programming experience (preferred).
Understanding of listed and OTC markets for D1, equities options, and volatility indices.
Experience in local and/or stochastic volatility models implementation (preferred).
Knowledge of statistics, including time series analysis and regressions.
Experience building trading tools (preferred).
Experience in alpha research and signal generation (preferred).
London, United Kingdom+1124 days ago
$200,000–$275,000
Python
C++
Quantitative Trading Systems
back testing
Simulation
Performance Testing
Market Data
Excel
Derivatives Modeling
Alpha Research
Signal Generation
Convertible Bonds
CMBS
CLO
ABS
London, United Kingdom+2124 days ago
$200,000–$225,000
C++
Python
SQL
NoSQL
Stochastic Modeling
Time Series Analysis
Optimization
Machine Learning
Numerical Methods
Linear Algebra
Statistics
Probability
Simulation
Distributed Data Workflows
DAG-based Systems
Forecasting
Data Analysis
Python
SQL
Quantitative Modeling
Portfolio Construction
Equity Markets
Data Extraction
Version Control
Reproducible Pipelines
Risk Modeling
Market Microstructure
Data Quality
Research Infrastructure
Analytics
Python
C++
Distributed Systems
Linux
Low-latency Systems
Data Processing
Machine Learning
Numerical Computing
Simulation
Optimization
Cloud Infrastructure
GPUs
Time-series Analysis
Data Platforms