This role pays more than
86%
of similar roles. Most pay
$131,225–$200,187
— the shaded band above.
At the midpoint, this role pays about
$225k
versus about
$166k
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
187 open roles
on FindRole.
Listed pay typically runs
$130,000–$250,000
across 60 roles with salary data.
Join our FICC Quantitative Research team as an Associate or VP in New York, where you will lead the development of market making and quoting strategies across various FICC products. Your day-to-day involves applying advanced statistical analysis and quantitative techniques like neural networks and machine learning to build models that drive systematic alpha strategies for real-time trading decisions. You will also implement risk management frameworks, calibrate models using large datasets, and collaborate with developers to enhance core analytics infrastructure. Additionally, you’ll develop pricing, trading, and risk tools, leveraging data to optimize market making and hedging strategies. Ideal candidates have a strong background in quantitative fields such as physics or mathematics, along with programming skills in languages like Python, Java, or C++. Effective communication skills are essential for articulating complex concepts to both technical and non-technical stakeholders.
Python
C++
R
Machine Learning
Alternative Data
Quantitative Investment Strategies
Equity Derivatives
Statistical Learning
Market Structure
Documentation
Communication Skills
Presentation Skills
Python
C++
Java
Bayesian analysis
Time series analysis
Machine learning algorithms
Linear Regression
Data management tools
Risk management
Scenario-based analysis
Statistics
Performance analysis
Econometric techniques
C++
Java
Python
Bayesian analysis
Time series analysis
Machine learning algorithms
SQL
MongoDB
REST
Spring
Unix environment
Micro-services architecture
Full software development lifecycle
NoSQL technologies
Python
KDB
C++
Java
AI
ML
equity derivatives
volatility products
option trading
derivatives pricing
risk management
backtesting
attribution
regime analysis
fundamental features
quantitative features
microstructure features
Greeks
scenarios
signal research
market data
alpha capture
risk warehousing
statistical modeling
machine learning