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.