Associate, Quantitative Engineering

Goldman Sachs

Quick summary

Work type: On-site
Location: New York, NY
Salary: $113,000–$155,600 / yr
Posted: 1 day ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $184k

This role $134k

$100k most similar roles pay here $238k

This role pays less than 78% of similar roles. Most pay $142,475–$225,000 — the shaded band above. At the midpoint, this role pays about $134k versus about $184k 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.

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View all roles at Goldman Sachs

At a glance

TL;DR · Associate, Quantitative Engineering

Role Posting Log in to save

As an Associate on the Applied AI Team within Global Banking & Markets at Goldman Sachs in New York, you will deploy AI-based quantitative technologies to drive revenue generation and innovation. Your day-to-day responsibilities include designing, training, and deploying scalable AI models for tasks like time series forecasting and market making, while collaborating with various teams to address unique challenges in the financial sector. You will leverage advanced knowledge in computer science, statistics, artificial intelligence, and machine learning to enhance model performance through experiments and analysis. The role requires expertise in Python or C++, proficiency in ML libraries such as TensorFlow and PyTorch, experience with big data technologies like Kubeflow, and a solid understanding of financial markets and MLOps practices.

Skills

Python C++ Java TensorFlow PyTorch scikit-learn Keras Kubeflow MLflow Time Series Forecasting MLOps Big Data Technologies Financial markets Market making Asset pricing Machine Learning Deep Learning Large Language Models

What you'll do

Design and deploy AI models to drive revenue generation in financial markets.
Train scalable AI systems for Time Series Forecasting and market making.
Conduct experiments to enhance the performance of machine learning models.
Develop high-quality, production-ready code using ML libraries like TensorFlow.
Collaborate on pioneering projects that integrate artificial intelligence with finance.
Maintain and improve MLOps tools such as Kubeflow or MLflow in production.

What we're looking for

Master’s degree in Computer Science or equivalent quantitative field and 1 year of AI Quantitative role experience.
Bachelor’s degree in related field and 3 years of relevant AI/ML experience.
Proficiency in C++, Java, or Python programming languages.
Expertise in machine learning libraries and frameworks like TensorFlow, PyTorch.
Experience with big data technologies and MLOps tools such as Kubeflow or MLflow.
Strong background in financial markets, market making, and asset pricing.

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