Asset & Wealth Management, QIS Alternatives Analyst, New York

OUR IMPACT 

Goldman Sachs Asset Management (GSAM) is one of the world’s leading investment managers. GSAM provides institutional and individual investors with investment and advisory solutions, with strategies spanning asset classes, industries, and geographies.  We help our clients navigate today’s dynamic markets, and identify the opportunities that shape their portfolios and long-term investment goals. We extend these global capabilities to the world’s leading pension plans, sovereign wealth funds, central banks, insurance companies, financial institutions, endowments, foundations, individuals and family offices

The Quantitative Investment Strategies (QIS) group in GSAM is a market leader in quantitative portfolio management. We use advanced quantitative methods to structure, manage, and monitor investment portfolios. Within QIS, the QIS Alternatives team delivers hedge fund beta strategies, systematic multi-asset alternative strategies, and options-based solutions to investors.

We are seeking an outstanding junior candidate that is passionate about investment and motivated to find ways to express options-based investment ideas across asset classes in a systematic manner. Members of QIS work closely together in teams of junior and senior professionals, providing a unique quantitative research environment in which to learn and apply advanced financial and econometric methods.

Key responsibilities include:

• Conduct quantitative research on systematic, cross-asset volatility.
• Monitor systematic volatility premia models on an ongoing basis to ensure expected return delivery within expected risk parameters.
• Manipulate structured and unstructured large datasets to extract quantitatively based insights for systematic investment strategies.
• Contribute to the development, enhancement, and maintenance of the research and portfolio management platform, encompassing strategy backtesting, performance monitoring, and risk analysis.

Skills and experience we’re looking for:

• BA/BS Degree in Financial Engineering, Statistics, Mathematics, or Computer Science
• Excellent analytical and quantitative skills
• Solid understanding of statistics, linear algebra, and calculus
• Previous exposure to machine learning or artificial intelligence
• Strong programming skills (Python, Matlab, R, Perl, C++, Java, or other languages)
• Basic understanding of systematic investing
• Creativity and ability to think outside the box
• Ability to work well in a team-oriented, fast-paced environment
• Keen attention to detail

ABOUT GOLDMAN SACHS 
 
At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world.  
 
We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs. Learn more about our culture, benefits, and people at GS.com/careers.  
 
We’re committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process. Learn more:https://www.goldmansachs.com/careers/footer/disability-statement.html 

Salary Range 
The expected base salary for this New York, New York, United States-based position is $90000-$125000. In addition, you may be eligible for a discretionary bonus if you are an active employee as of fiscal year-end.

Benefits 
Goldman Sachs is committed to providing our people with valuable and competitive benefits and wellness offerings, as it is a core part of providing a strong overall employee experience. A summary of these offerings, which are generally available to active, non-temporary, full-time and part-time US employees who work at least 20 hours per week, can be found here.