Quantitative Developer - Commodities Risk

This role is to support the risk team with technology and quantitative solutions for the calculation, aggregation and interpretation of risk metrics such as VaR, Greeks, shock scenarios, PFE and similar.

Responsibilities

Develop and use Python libraries and tools to run a range of risk-specific tasks, such as:

Processing large and complex quantities of data, both historical and real-time
Collecting, massaging, smoothing and analyzing timeseries
Using optimization and statistical techniques with historical data to calibrate models for the dynamics of commodities curves
Gain familiarity with additional internal analytical libraries and tools and use them as building blocks for VaR and similar analysis

Mandatory Requirements

Previous Python development experience (pandas/numpy)
Experience with AWS or other cloud platforms
Experience with financial mathematics and statistics
Able to work independently in a fast-paced environment
Strong analytical and problem solving capabilities
Detail oriented, organized, demonstrating thoroughness and strong ownership of work

Preferred Requirements

Familiarity with commodities markets in general, and with concepts such as seasonality, contango/backwardation, calendar and basis spread dynamics, correlation surfaces and volatility skew.
Familiarity with typical financial products, derivatives and their risk profiles is another plus.