Asset & Wealth Management, MAS, PM Infrastructure and AI Data Strategy, Associate - New York

Core Responsibilities

Build deep domain fluency across MAS portfolio management, trading, risk, and PM Infrastructure to translate investment workflows into clear data and technology requirements.

Own MAS data strategy and governance across structured and unstructured data (standards, definitions, lineage, controls, stewardship) to improve reliability, reuse, and auditability.

Lead end-to-end data discovery and mapping across business functions—positions, risk, performance, and reference data—to produce a prioritized roadmap to close data gaps across public and private markets.

Define build-ready requirements and acceptance criteria for PM Infrastructure & AI initiatives, including data quality thresholds, validation rules, and rollout readiness checks.

Design and execute rigorous testing and output validation for PM Infrastructure & AI builds (reconciliations, edge cases, regression testing) to ensure results meet business expectations and performance benchmarks.

Identify and scale high-impact opportunities for data and intelligent automation in PM workflows, partnering daily with PMs, Traders, Risk, and Engineering from prototype through production.

Create executive-ready reporting for the Head of PM Infrastructure & AI Strategy—recurring status updates and dashboards that translate technical progress into decisions, risks, and next steps for senior leadership.

Basic Requirements

• Bachelor's degree required in a quantitative, technical, or finance-related field (e.g., Computer Science, Data Science, Statistics, Economics, Engineering, or Mathematics).
• 2–4 years of relevant experience in investment management, data science, business intelligence, project management, or a data-focused role within financial services or asset management.
• Excellent project management skills.
• Solid understanding of data concepts including data modeling, data quality frameworks.
• Experience with Python similar scripting languages for data manipulation and analysis is a plus.
• Advanced knowledge of AI/ML concepts, including how data quality and structure impact model performance.
• Strong written and verbal communication skills, with the ability to document technical processes clearly and present findings to both technical and non-technical audiences.
• Highly organized and detail-oriented, with the ability to manage multiple concurrent tasks, meet deadlines, and operate effectively in a fast-paced, collaborative environment.
• Proactive and self-motivated, comfortable taking direction while also identifying issues and opportunities independently.
• Advanced degree, CFA progress, or relevant data certifications a plus.

Pay

The expected base salary for this New York, New York, United States-based position is $100000-$160000. In addition, you may be eligible for a discretionary bonus if you are an active employee as of fiscal year-end.

Benefits

Goldman Sachs is committed to providing our people with valuable and competitive benefits and wellness offerings, as it is a core part of providing a strong overall employee experience. A summary of these offerings, which are generally available to active, non-temporary, full-time and part-time US employees who work at least 20 hours per week, can be found here.