Quantitative Researcher in Commodity Risk

We are looking for an outstanding Quantitative Researcher to join our Commodities Risk Management team reporting to the Head of Commodity Risk Analytics.

Responsibilities include:

• Formulate and implement models for onboarding new commodity products and derivatives, such as methodologies for constructing volatility surfaces and modeling physical assets.

• Be responsible for quality of risk metrics, such as vol calculation methodology.

• Develop methodologies and procedures to conduct historical and hypothetical stress testing, as well as analysis of the results using standardized statistical metrics.

• Work with Risk Management and Risk Tech to configure and calibrate risk systems, particularly for new products and physical assets.

• Apply quantitative methods to solve risk topics, such as estimating market liquidity and liquidation costs.

• Contribute to overall risk management team at BAM in risk analytics, processes, and reporting. This may involve ad-hoc risk analysis for portfolios that are not commodities-focused or investigation of impact of a commodities-focused portfolio to the overall risk of the firm.

• Contribute to Global Risk Committee’s understanding of risk drivers and considerations in related markets.

• Improve and extend existing risk reporting tools, including risk analysis, P&L attribution, and portfolio construction, with focus on both regular periodic reporting and ad-hoc requests.

Requirements

• At least 5+ years of experience, with 10+ years preferred, as a commodities quant, strategist, or quantitative risk officer, at a physical energy trading firm.

• Strong academic background (masters/doctorate) in quantitative fields such as math, physics, engineering, statistics, economics, or finance.

• Skilled in valuing and modeling physical commodity assets and structured transactions, such as gas or oil storage and pipeline transport, power tolls, transmission, etc.

• Experience with as many of the following commodities as possible: electricity, congestion markets, natural gas, crude oil, oil products, energy assets, agricultural commodities, structured transactions, shipping.

• Experience with seasonality in commodities risk models.

• Strong programming skills in Python and SQL. Must be familiar with numeric libraries such as pandas, numpy, etc.

• Strong problem-solving skills.

• Enjoy working in a collaborative environment and able to communicate complex ideas clearly

Nice to have

• Advanced Python knowledge including management of virtual environments, release process, or multi-processing

• Experience developing Plotly Dash dashboards and other data visualization tools

• Experience working at a hedge fund or other asset management firms with exposure to systematic futures strategies or portfolio construction

• Experience with factor analysis, PCA, decomposition models for P&L and risk, machine learning

• Experience in working with Beacon risk system

Quantitative Researcher - Commodity Risk