below marketmost similar roles pay hereabove market
This role pays more than
72%
of similar roles. Most pay
$152,150–$217,412
— the blue band above.
At the midpoint, this role pays about
$212k
versus about
$185k
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 Quant Researcher, Commodities joins the Commodities team to develop quantitative models and analytical frameworks supporting physical commodity transport, storage, and logistics. This front-office role involves building tools for scenario analysis, forecasting, optimization, and valuation while translating market structures and infrastructure constraints into rigorous research. You will partner with engineers, portfolio managers, and traders to generate market insights and actionable trade ideas. Required technical skills include C++ for high-performance libraries and Python for research and data analysis. Candidates must possess strong grounding in probability, statistics, linear algebra, and numerical methods, with experience in time series analysis and stochastic modeling. The work focuses on energy markets, inventory economics, freight constraints, and regional infrastructure bottlenecks to solve complex problems regarding physical optionality and logistics.
Develop quantitative models and analytical frameworks for new and existing commodity products.
Build tools for scenario analysis, forecasting, optimization, and valuation.
Translate market structures and infrastructure constraints into rigorous quantitative research.
Generate differentiated market insights and actionable trade ideas for portfolio managers and traders.
Contribute to the research architecture and analytics platform used by the investment team.
Design and integrate models into front-office risk platforms and pricing tools.
Formulate ambiguous market questions into testable hypotheses and practical research outputs.
What we're looking for
PhD, MSc, or BSc in a highly quantitative discipline such as mathematics, physics, computer science, engineering, statistics, economics, or operations research.
At least 5 years of experience in a quantitative research, commodities, logistics, or applied modeling environment.
Strong C++ skills with experience building high-performance analytical libraries and models.
Strong Python skills for research, prototyping, data analysis, and workflow orchestration.
Strong grounding in probability, statistics, linear algebra, optimization, and numerical methods.
Experience with quantitative approaches such as time series analysis, forecasting, simulation, optimization under constraints, network and flow models, and stochastic modeling.
Experience in, or strong interest in learning about, physical commodity markets, with emphasis on energy markets.
Prior experience in front-office quantitative, trading, or investment-oriented roles (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
Python
C++
Machine Learning
Deep Learning
Reinforcement Learning
High-Frequency Trading
Market Microstructure
Quantitative Research
Signal Research
order-book modeling
Financial Engineering
data-analysis
Live Trading Systems
C++
Python
ML Infrastructure
Low-Latency Engineering
Distributed Systems
PyTorch
JAX
CUDA
Kubernetes
Kafka
Spark
Ray
Linux Performance Engineering
order-management systems
market-data normalization
Backtesting
model-serving
GPU Clusters
Lock-free Programming
PyTorch
JAX
Transformer
Time-series Foundation Models
Distributed Training
Machine Learning
Data Pipelines
Mixed Precision
model-serving
Optimization
Quantitative Trading
HFT
Electronic Market Making
Statistics
Operations Research