Asset & Wealth Management - Analyst Quantitative Strategist in Wealth Management Strats
Our quantitative strategists are at the cutting edge of our business and solve real-world problems through a variety of analytical methods. As a member of our team, you will utilize your training in mathematics, programming, and logical thinking to build quantitative models that drive success in our business. Your problem-solving talents and aptitude for innovation will help define your contributions and enable you to find solutions to a broad range of problems, in a dynamic, fast-paced environment.
Responsibilities
As a strategist on our PWM Risk Stratsteam, you will work closely with a range of teams within the Asset and Wealth Management Division and across the firm. Collaboration involves various teams across risk management, fraud strategy and leadership. You will combine quantitative techniques and industry knowledge to build best in class models and tools that streamline risk management, detect fraud at scale, enable optimized data-driven business decision making, and optimize profitability.
Responsibilities include:
- Risk Management: Develop quantitative stress based models and tools to manage firm's counterparty credit risk management in wealth management.
- Delivering valuation, risk metrics and quantitative analytics for financial and non-financial risks across wealth management
- Developing and deploying ML models for fraud and anomaly detection as well as business workflows enhancement
- Collaborating on the design of new and existing strategies to address clients' investment goals.
- Developing and maintaining risk management and portfolio analysis tools across multiple asset classes for senior risk managers.
- Building and maintaining infrastructure of Strategists' analytical systems.
- Building and maintaining robust and systematic risk management tools and reporting
About Goldman Sachs Wealth Management
Across Wealth Management, Goldman Sachs helps empower clients and customers around the world to reach their financial goals. Our advisor-led wealth management businesses provide financial planning, investment management, banking, and comprehensive advice to a wide range of clients, including ultra-high net worth and high net worth individuals, as well as family offices, foundations and endowments, and corporations and their employees. Our consumer business provides digital solutions for customers to better spend, borrow, invest, and save. Across Wealth Management, our growth is driven by a relentless focus on our people, our clients and customers, and leading-edge technology, data, and design.
Basic Qualifications
- Bachelor, Masters or Ph.D. in a quantitative or engineering field, e.g. mathematics, physics, quantitative finance, computational finance, computer science, engineering
- Programming and mathematical skills are required
- Creativity, problem-solving skills, and ability to communicate complex ideas to a variety of audiences
- A self-starter, should have ability to work independently as well as thrive in a team environment
Preferred qualifications:
- Excellent understanding of machine learning techniques and algorithms, such as gradient boosting decision trees, random forests, etc., is a plus
- Experience with building models using common data science toolkits, i.e., Python (Pandas, NumPy, Scikit-learn) and Spark
- Previous work experience in: Utilizing statistical methods, including time-series and regression analysis; programming in object-oriented languages for efficient model implementations; manipulating data sets using relational databases and SQL
ABOUT GOLDMAN SACHS
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