Job Description
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
Within GSAM, the Quantitative Investment Strategies (QIS) group is responsible for managing client assets, and is a market leader in quantitative portfolio management.
We use advanced quantitative methods to structure, manage, and monitor investment portfolios including mutual funds, and separately managed accounts.
QIS offers multi-asset strategies, as well as equity strategies, including both actively managed portfolios and portfolios that closely track an index.
Clients include public, corporate and charitable institutions, high net-worth individuals, retail investors, and various portfolio management groups within the division.
HOW YOU WILL FULFILL YOUR POTENTIAL
The ideal candidate is passionate about investment and motivated to outperform the market. We welcome individuals who are excited by the prospect of combining creative insights with extensive research to make good investment decisions.
Key responsibilities include :
Alpha research : Generate creative research ideas, explore new datasets, conduct rigorous analysis, and implement quantitative trading models.
Research in model and optimization related techniques.
Portfolio management : Assume full responsibility for alpha model, portfolio construction, and performance. Oversee day to day systematic trade generation and execution.
SKILLS & EXPERIENCE WE'RE LOOKING FOR
- Degree (Undergraduate / Masters) in a highly computational and quantitative discipline. Advanced degree preferred.
- 1+ years of experience in a relevant field.
- Strong understanding of machine learning, artificial intelligence, and / or optimization techniques.
- Strong programming skills (i.e. Python, Matlab, C++, Java, or other languages)
- Strong understanding of statistics and linear algebra.
- Creativity and ability to think outside the box
- Ability to work well in a fast-paced environment
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.
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