Goldman Sachs Asset Management is one of the world's leading asset management institutions. GSAM delivers innovative investment solutions managing more than One Trillion US Dollars on a global, multi-product platform. Our products include Hedge Funds, Private Equity, Fund of Funds, Quantitative Strategies, Fixed Income, Fundamental Equity and a Global Portfolio Solutions Business. GSAM Technology is directly aligned to the business. Software is engineered in a fast-paced, dynamic environment, adapting to market and customer needs to deliver robust solutions in an ever-changing business environment. GSAM Technology builds on top of cutting edge in-house platforms complimented with a strong focus on leveraging open source solutions.
The GSAM QIS team manages over $100 billion across a variety of mandates including institutional portfolios, mutual funds and hedge funds, using sophisticated quantitative models that have been developed in an innovative research environment. The group is one of the largest direct quantitative managers in the world, and is recognized as an industry leader in quantitative portfolio management techniques. The team manages exposures to global stock, bond, currency and commodity markets to generate alpha and advanced beta strategies for our Clients' portfolios. As one of the longest-running quantitative teams in the industry, QIS has developed a strong reputation for innovation, excellence and teamwork.
The QIS engineering team, working in a close-knit environment with Portfolio Managers, designs and develops the proprietary platforms that drive the QIS business, spanning alternative data acquisition, quantitative research, model generation, portfolio construction and trading. This role will focus on building out tools and infrastructure to service QIS clients, including performance attribution, after tax reporting, client reporting, ESG portfolio analysis, custom portfolio analysis. Open to a variety of the skillsets required to build out our team - big data ingestion and management, machine learning, search, data APIs, visualization. Quant skills not required - this is a technology problem. Broad range of technologies employed: Hadoop, Spark, Kafka, Elastic, Java, Scala, Python, Notebooks, JSI web stack, various visualization toolkits. For context, think quandl.com/quantopian.com but for GS.
RESPONSIBILITIES AND QUALIFICATIONS
HOW YOU WILL FULFILL YOUR POTENTIAL• A chance to build a new tools and infrastructure with enormous scope to innovate and transform QIS business capabilitySKILLS AND EXPERIENCE WE ARE LOOKING FOR• Driven to be a world class engineer