below marketmost similar roles pay hereabove market
This role pays less than
57%
of similar roles. Most pay
$125,962–$202,750
— the blue band above.
At the midpoint, this role pays about
$148k
versus about
$164k
for comparable roles.
Based on 240 similar postings.
Employer
About Goldman Sachs
Goldman Sachs is a leading global investment banking, securities, and investment management firm providing financial services to corporations, financial institutions, governments, and individuals.
Goldman Sachs currently has
81 open roles
on FindRole.
Listed pay typically runs
$130,000–$250,000
across 37 roles with salary data.
The Asset & Wealth Management - Quantitative Strategist - Associate - New York joins the PWM Risk Strats team to solve complex financial problems using analytical methods. This role involves developing and deploying machine learning models for fraud detection, anomaly detection, and business workflow enhancements. You will build systematic risk management tools, deliver quantitative analytics for financial and non-financial risks, and create AI-led solutions to improve accuracy. Key responsibilities include maintaining analytical infrastructure and designing strategies to meet investment goals across multiple asset classes. Required skills include programming in object-oriented languages, SQL, and data science toolkits like Python, Pandas, NumPy, Scikit-learn, and Spark. You must apply statistical methods such as time-series and regression analysis while utilizing techniques like gradient boosting decision trees, random forests, prompt engineering, and LLM models.
Develop and deploy ML models for fraud detection and anomaly detection.
Deliver risk metrics and quantitative analytics for financial and non-financial risks.
Create AI-led solutions to improve efficiency and accuracy in risk management.
Build and maintain systematic risk management tools and reporting systems.
Develop risk management and portfolio analysis tools across multiple asset classes.
Build and maintain the infrastructure of the strategists' analytical systems.
Design new and existing strategies to address specific client investment goals.
What we're looking for
Bachelor, Master, or Ph.D. in a quantitative or engineering field such as mathematics, physics, quantitative finance, computational finance, computer science, or engineering.
1-3 years of experience in the job offered or related quantitative financial modeling and software development positions.
Proficiency in programming and mathematical skills.
Experience with building models using common data science toolkits including Python (Pandas, NumPy, Scikit-learn) and Spark (preferred).
Experience with prompt engineering, working with LLM models, and MCP (preferred).
Previous work experience utilizing statistical methods including time-series and regression analysis (preferred).
Previous work experience programming in object-oriented languages for efficient model implementations (preferred).
Previous work experience manipulating data sets using relational databases and SQL (preferred).
Python
Java
Machine Learning
Artificial Intelligence
Big Data
Data Analytics
Portfolio Construction
Factor Analytics
FICC
Equity
Software Development
AI Tools
Python
C++
Machine Learning
Deep Learning
Reinforcement Learning
High-Frequency Trading
Market Microstructure
Quantitative Research
Signal Research
order-book modeling
Financial Engineering
data-analysis
Live Trading Systems