Remote Quantitative Risk Lead

Summary

Join the Finance team at IFT as a Quantitative Risk Lead to take responsibility for quantifying, tracking, and reporting financial risks that the organisation is exposed to. As an ecosystem of Web3 projects, the role will support the material treasury of the entire organisation.

Requirements

• Excellent software development skills (ideally, Python- open to other languages), including a strong bias towards automation, documentation and testing
• Structure and rigour in their thinking
• Degree in a quantitative discipline (STEM, economics, finance)
• Productive while working remotely and autonomously, initially in a risk quant “team of 1”
• A strong alignment to our principles: https://status.im/about/#our-principles

Responsibilities

• Identifying and quantifying financial and economic risks that the treasury is exposed to
• Owning the development and maintenance of quantitative risk models for the treasury (e.g. Historical VaR, Monte Carlo VaR, Multi-Factor Risk Models, Stressed VaR, Liquidity Risk models, etc)
• Building the data gathering and risk monitoring infrastructure, including on-chain monitoring of smart contracts
• Performing advanced statistical analysis on underlying risk factors (returns’ distribution, volatility, correlations)
• Supporting the build out of an internal quantitative tool stack (e.g. asset models, simulation engines, forecasting and reporting, scenario analysis, etc)
• Assisting in the development of dashboards and reports to put quantitative risk information at the centre of financial decision making

Preferred Qualifications

• Deep knowledge of the specific financial and quantitative risks faced by a web3 organisation with a large, on-chain, multi-asset crypto treasury (i.e. must be able to independently identify them, not just quantify the risks that others ask them to)
• Previous professional experience with smart contract development
• Previous professional experience building similar quantitative risk tech stacks
• A security mindset

Benefits

The expected compensation range for this role is $90,000 - $140,000 (negotiable, dependent on how we assess your skills and experience throughout our interview process)