An Industry-leading hedge fund with around 100 billion in AUM is looking to grow out their Commodities Quantitative Risk Analytics platform in a full team-buildout that will assist of the Head of Commodity Quant Risk Analytics in building out all methodology and infrastructure from scratch so that they can begin physical trading. This quantitative researcher will be working directly with the Head of the Group in a hands-on, front-office facing role focused on the North American Power & Gas markets.
Aside from building out all the methodology and risk infrastructure to help launch the firm's trading activities, this hire will also be tasked with working directly with Portfolio Managers and traders to build quantitative pricing and risk models for commodity trading and taking part in quantitative research focused on portfolio construction and investments improvement. This is a hands-on role focused on building out the commodity trading business and framework from scratch.
The fund is looking for candidates of the most quantitative nature, with at least 5-10+ years of experience as a commodities quant developing risk and pricing models. Proficiency in Python and developing dashboards or data visualization tools will be required as well as a Master's or Doctorate in a relevant quantitative field.
- Hands-on buildout of the entire methodology and risk infrastructure for the commodities trading business
- Building pricing and VaR models for commodity trading with a focus on North American Power & Gas
- Working directly with Portfolio Managers and Traders on quantitative and business strategies
- Quantitative research focused on portfolio constriction and investments improvement
- At least 5-10+ years of experience serving as a commodities quant or quant risk officer at a physical energy trading firm
- Prior experience developing risk and pricing models for commodities products
- Proficiency in Python
- Experience developing dashboards and data visualization tools
- A Master's or PhD Degree in a relevant quantitative field