This role pays more than
69%
of similar roles. Most pay
$140,000–$225,000
— the shaded band above.
At the midpoint, this role pays about
$212k
versus about
$182k
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
59 open roles
on FindRole.
Listed pay typically runs
$175,000–$250,000
across 30 roles with salary data.
The Quant Researcher, Commodities joins the front-office team to develop quantitative models and analytical frameworks supporting the commodities business, including physical transport, storage, and logistics. Working alongside engineers, portfolio managers, and traders, the researcher builds tools for scenario analysis, forecasting, optimization, and valuation while translating infrastructure constraints into rigorous research. The role requires proficiency in C++ for high-performance libraries and Python for prototyping and data analysis. Candidates must possess strong skills in probability, statistics, linear algebra, and numerical methods to address complex market problems. Key technical areas include time series analysis, stochastic modeling, and network flow models. The work focuses on the physical commodity markets, specifically energy, where the researcher addresses inventory economics, freight constraints, and infrastructure bottlenecks to generate actionable trade ideas and contribute to the core research architecture used by the investment team.
Develop quantitative models and analytical frameworks for new and existing commodity products.
Build tools for scenario analysis, forecasting, optimization, and valuation of commodities.
Translate physical infrastructure constraints and market realities into rigorous quantitative research.
Generate differentiated market insights and actionable trade ideas for portfolio managers and traders.
Contribute to the development of the research architecture and analytics platform used by the investment team.
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.
Strong C++ skills with experience building high-performance analytical libraries and models.
Strong Python skills for research, prototyping, data analysis, and workflow orchestration.
At least 5 years of experience in a quantitative research, commodities, logistics, or applied modeling environment.
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/flow models, and stochastic modeling.
Experience in, or strong interest in learning about, physical commodity markets, especially energy markets (exposure to oil, gas, power, metals, or agriculture is a plus).
Prior experience in front-office quantitative, trading, or investment roles; familiarity with SQL/NoSQL, distributed data workflows, and machine learning are preferred.
C++
Python
PyTorch
JAX
CUDA
Kubernetes
Kafka
Spark
Ray
Distributed Systems
Low-latency Engineering
Linux Performance Engineering
order-management systems
market-data normalization
Backtesting
Profiling
Concurrency
Transformer
PyTorch
JAX
Machine Learning
Distributed Training
Quantitative Trading
Data Pipelines
Signal Research
Market Microstructure
Portfolio Construction
Risk Management
Benchmarking