At Goldman Sachs, quantitative strategists are renowned for their expertise in building and developing quantitative and technological solutions to tackle complex analytical challenges. As a Portfolio Analytics strategist, you'll collaborate closely with trading desks and the business to define, implement, and manage all the analytics required to enhance decision-making and maintain a competitive edge. This includes real-time pricing, risk analytics, large-scale analysis, and optimizations, along with addressing technical challenges in a scalable manner. Being a strategist means being at the heart of the action on the trading floor, staying aware of and reacting to market environments, and working closely with key business stakeholders.

Your impact:

As a portfolio analytics strategist, you'll work with trading desks and desk strategists to integrate pricing models into state-of-the-art risk management tools. You'll be a key partner for the business on all risk management topics. This unique position sits at the intersection of mathematical models and real-life implementation, allowing you to make a significant impact by mastering the connection between the two. Strategists are at the core of business activities, constantly collaborating with colleagues from multiple regions and adjacent analytical teams to develop scalable, cutting-edge technology.

Responsibilities:

• Develop cutting edge risk management capabilities, providing fast and reliable tools for different desks and businesses.
• Perform systematic and quantitative analysis of different markets and implement the most optimal risk calculations accordingly.
• Work closely with trading and providing support for the risk management systems.
• Be involved with all stages of the software development life cycle with a range of technologies and collaborate closely with engineering teams who support the underlying infrastructure and frameworks.

Qualifications:

• Excellent academic background in a quantitative field such as mathematics, physics, statistics, or computer science. A major in computer science with an interest in quantitative topics, or a quantitative background with a strong interest in implementation, is preferred. 
• Strong programming skills in an object oriented or functional paradigm such as C++, Java or Python.
• Self-starter with strong self-management skills, ability to manage multiple priorities and work in a high-paced environment.
• Excellent written and verbal communication skills.
• Experience up in finance or a cutting-edge technology company is a plus.
• Experience in building risk management systems (irrespective of asset class) is also a plus. 
• Previous quantitative or technical role working on or with a derivatives trading desk (irrespective of asset class) is also a plus.