Wealth Management-Quantitative Engineering-Analyst-Dallas

Goldman Sachs • Dallas, TX

3d

About The Position

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.

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.

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.

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.

Requirements

• Bachelor or Masters 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
• 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

Responsibilities

• 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
• Building and maintaining robust and systematic risk management tools and reporting
• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Number of Employees: 5,001-10,000 employees