Risk Application Support Engineer

Responsibilities:

• Live Risk monitoring and management with attention to follow up tasks and postmortems across the firm
• Startup and oversight over a variety of risk calculation engines, each with differing inputs and outputs important at different hours of the trading day (24/5 global coverage across team)
• Switch between deployment, automation, monitoring enhancement, and scripting/coding bigfixes in all Verition environments, such as in AWS, on-prem Linux & Windows hosts, external vendor facing network connections, etc.
• Ownership of production risk footprint, e.g. identify system improvements, automate daily tasks, document existing and new workflows
• Integration with Trading Operations as whole to ensure that all trades are captured and calculated

Qualifications:

• A Bachelor's Degree from an accredited college or university (CS, Math, Engineering preferred)
• Hands on experience as a Risk Engineer, having worked directly with Risk Managers and Product Control in a live production environment. Integration with vendor product calculation engines.
• Technical proficiency with Python, Linux, Windows, SQL, Excel, AWS, Airflow; ability to debug scripts and code in BASH, Python, PowerShell
• DevOps experience with Jenkins, Ansible, Git, Bitbucket, Jira, Docker is a plus
• Strong analytical and detail-oriented aptitude; a high degree of accuracy is required
• Excellent communication and organizational skills with friendly demeanor
• Ability to manage time effectively, set priorities and meet deadlines, mentorship of junior members

Preferred:

• Experience in coursework or professional career: calculations for Volatility, Options: Greeks Black-Scholes-Merton equation (martingales), Value-at-Risk, pricing and Candles, ETP valuation vs underliers, and more
• Heightened awareness for production alerts and adhere to SLA for remediation
• Experience with DataDog/Zabbix/PagerDuty and application monitoring frameworks
• Experience with Redwood RunMyJob and familiarity with Cron, or similar job scheduling frameworks such as Control-M, Tidal