This role pays less than
90%
of similar roles. Most pay
$159,812–$235,750
— the shaded band above.
At the midpoint, this role pays about
$130k
versus about
$198k
for comparable roles.
Based on 239 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
134 open roles
on FindRole.
Listed pay typically runs
$137,000–$250,000
across 55 roles with salary data.
Asset & Wealth Management, MAS, PM Infrastructure and AI Data Strategy, Associate - New York is a role within the Multi-Asset Solutions team that sits at the intersection of data, AI, and portfolio management infrastructure. You will partner with leadership to drive the firm's data strategy while building core platform components for investment workflows. Day-to-day responsibilities include profiling and mapping positions, risk, performance, and reference data to improve reliability and prototype scalable AI-enabled automation. You will manage data governance across structured and unstructured sources, define requirements for infrastructure initiatives, and execute rigorous testing for new builds. The role requires a background in quantitative or technical fields, proficiency in Python or similar scripting languages, and advanced knowledge of AI/ML concepts. This position addresses the challenge of leveraging high-quality data to enhance investment outcomes and automate complex portfolio management processes.
Translate investment workflows into clear data and technology requirements for portfolio management, trading, and risk functions.
Own the MAS data strategy and governance for structured and unstructured data to improve reliability and auditability.
Lead end-to-end data discovery and mapping across positions, risk, performance, and reference data.
Define build-ready requirements and acceptance criteria for PM Infrastructure and AI initiatives.
Execute rigorous testing and output validation for new infrastructure builds to ensure they meet business benchmarks.
Identify and scale high-impact opportunities for intelligent automation within portfolio management workflows.
Create executive-ready reporting and dashboards to communicate technical progress and risks to senior leadership.
What we're looking for
Bachelor's degree in a quantitative, technical, or finance-related field.
2–4 years of experience in investment management, data science, business intelligence, project management, or a data-focused role in financial services.
Solid understanding of data concepts including data modeling and quality frameworks.
Advanced knowledge of AI/ML concepts and how data structure impacts model performance.
Strong written and verbal communication skills to present findings to both technical and non-technical audiences.
Experience with Python or similar scripting languages for data manipulation and analysis (preferred).
Advanced degree, CFA progress, or relevant data certifications (preferred).