Software Engineer - Liquidity Risk

    • Bangalore, India

Manages global market risk by calculating Value-at-Risk (VaR) and Stress Tests. Those measures are used to present an accurate picture of the firmwide risk exposure, thereby
informing the firm's management and trading desks on how the day-to-day movements of the market will impact its balance sheet, and how to protect capital. VaR metrics are sent to the Fed & other global regulators on a regular basis.
Risk management is one of Goldman Sachs' core competencies, and is central to our continued success. Risk metric data volumes have grown rapidly in recent years and our systems need to provide flexible access and powerful analytics. Working with Liquidity Risk Technology, you will design and expand systems to drive the best senior management decisions.


• Understand business needs and hone your ability to translate them into a technical design and implementation
• Mentor junior development engineers while developing new skills of your own
• Influence architectural discussions and drive continuous improvement of the data platform
• Solve financial problems using a broad mix of tools and technologies

• Bachelors degree in Computer Science, Mathematics, Engineering, or related discipline
• Experience in software development, including a clear understanding of data structures, algorithms, software design and core programming concepts
• Expertise in Java/Scala
• Comfortable multi-tasking, managing multiple stakeholders and working as part of a team
• Excellent communication skills including experience speaking to technical and business audiences and working globally
• Strong problem solving and analytical skills
• Comfortable working in highly dynamic and rapid development environment
• Interest in financial markets and risk

Preferred Qualifications
• Experience with Hadoop v2, Spark, MapReduce, HDFS
• Familiarity with columnar databases like Sybase IQ
• Knowledge of web/RESTful service development: HTML 5, JavaScript, JSON
• Familiarity working in a Linux operating environment.
• Proficient working with large and complex code bases
• Experience with integration of data from multiple sources
• Understanding of market risk



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