The Core Engineering-Associate, Quantitative Strategist, Core Planning and Analysis Strats

Goldman Sachs Group; New York (NY); On-site; USD 115,000 - 180,000; Full time

Job summary

Goldman Sachs in New York, NY, seeks an Associate Quantitative Strategist in Core Planning and Analysis Strats to design and deploy advanced models for budgeting, forecasting, and balance sheet dynamics. You will build AI agents for automated analysis and decision support, leveraging Python and cloud deployment, with opportunities to explore Rust for performance-critical code.

The role targets recent PhD graduates and experienced Masters or Bachelors, with strong background in econometrics,

Qualifications

• Required field of study (U.S. or foreign equivalent, for all paths below): Statistics, Computer Science, Applied Mathematics, Physics, or a related quantitative field.
• PhD graduates with strong academic research backgrounds are highly preferred, but we will also consider experienced Masters and Bachelors. We value contributions to open source projects, publications, and other work and activities that provide evidence of exceptional ability.

Responsibilities

• Design, develop, implement, and document advanced quantitative models and scenarios for time-series forecasting of revenues, expenses, and balance sheet items. Incorporate a broad range of economic, financial, and business variables to address practical issues in budget planning and management, and conduct uncertainty quantification.
• Develop and deploy Statistical and explainable Machine Learning (ML) models for event prediction and forecasting. Derive actionable insights to support corporate strategy, budget planning, regulatory compliance, and internal governance reviews.
• Collaborate with cross-functional stakeholders across business divisions, Finance, Risk, and other core corporate departments. Translate complex user needs into precise model specifications, analytical metrics, interactive dashboards, and comprehensive reports tailored for senior leadership and operational teams.
• Execute the end-to-end model development lifecycle, encompassing data collection, exploratory data analysis, feature engineering, variable selection, model selection, hyperparameter tuning, validation, and scalable deployment on the Cloud.
• Design and engineer Artificial Intelligence (AI) agentic systems to deliver analytical, data science, and reporting capabilities through both interactive and batch reporting interfaces. Manage agent orchestration, context management, knowledge base integration, tool calling, and overall AI lifecycle management.
• Conduct rigorous simulation studies, provide theoretical justifications, and perform model performance testing. Create and maintain comprehensive technical documentation to support Model Risk Management (MRM) reviews, facilitate finding remediation, and ensure ongoing model monitoring.

Skills

Python

Rust

C++

Econometrics & Time-Series

Simulation & Uncertainty

Machine Learning

Causal Inference

Cloud Deployment

AI Agent Development

Education

PhD preferred

PhD in Statistics

PhD in Computer Science

PhD in Applied Mathematics

PhD in Physics

Tools

LangGraph

Google ADK

AWS Bedrock AgentCore

Job description

The Core Engineering-Associate, Quantitative Strategist, Core Planning and Analysis Strats

New York, NY, United States

Job Description

Role Overview

As an Associate Quantitative Strategist (Strat) within the Core Planning and Analysis Strats team, you will focus on two complementary mandates: (1) the design, development, and implementation of quantitative models to drive Budget Planning & Management — modeling and forecasting revenues, expenses, and balance sheet dynamics — and (2) the design and engineering of AI agents to automate analysis, reporting, and decision support across the planning lifecycle. You will build and deploy scalable solutions in the Cloud, primarily in Python, with opportunities to contribute to our growing adoption of Rust for performance-critical scientific computing.

This position is at the Associate level and is highly suited for recent PhD graduates looking to apply advanced mathematical, statistical, and computational techniques to real-world corporate planning and financial forecasting challenges, and to develop deep expertise in building AI agents for automated analysis.

Job Duties

• Design, develop, implement, and document advanced quantitative models and scenarios for time-series forecasting of revenues, expenses, and balance sheet items. Incorporate a broad range of economic, financial, and business variables to address practical issues in budget planning and management, and conduct uncertainty quantification.
• Develop and deploy Statistical and explainable Machine Learning (ML) models for event prediction and forecasting. Derive actionable insights to support corporate strategy, budget planning, regulatory compliance, and internal governance reviews.
• Collaborate with cross-functional stakeholders across business divisions, Finance, Risk, and other core corporate departments. Translate complex user needs into precise model specifications, analytical metrics, interactive dashboards, and comprehensive reports tailored for senior leadership and operational teams.
• Execute the end-to-end model development lifecycle, encompassing data collection, exploratory data analysis, feature engineering, variable selection, model selection, hyperparameter tuning, validation, and scalable deployment on the Cloud.
• Design and engineer Artificial Intelligence (AI) agentic systems to deliver analytical, data science, and reporting capabilities through both interactive and batch reporting interfaces. Manage agent orchestration, context management, knowledge base integration, tool calling, and overall AI lifecycle management.
• Conduct rigorous simulation studies, provide theoretical justifications, and perform model performance testing. Create and maintain comprehensive technical documentation to support Model Risk Management (MRM) reviews, facilitate finding remediation, and ensure ongoing model monitoring.

Minimum Education & Experience Requirements

Required field of study (U.S. or foreign equivalent, for all paths below): Statistics, Computer Science, Applied Mathematics, Physics, or a related quantitative field.

PhD graduates with strong academic research backgrounds are highly preferred, but we will also consider experienced Masters and Bachelors. We value contributions to open source projects, publications, and other work and activities that provide evidence of exceptional ability.

Special Skills Required to Perform the Job

Prior experience — satisfied through professional work or, for PhD candidates, graduate-level research, coursework, or dissertation work — must demonstrate the following:

• Programming Languages:Strong proficiency in Python. Experience with — or interest in developing — Rust (or C++) for performance-critical numerical code is a plus and aligns with the team's strategic direction.
• Econometrics & Time-Series Analysis:Modern econometric and time-series methods for multivariate forecasting and economic scenario generation, including state-space models, VAR/VECM and cointegration analysis, Bayesian VAR and dynamic factor models, structural identification, and nonlinear/regime-switching models.
• Simulation and Uncertainty Quantification:Monte Carlo simulation and modern Conformal Prediction methods for uncertainty quantification.
• Machine Learning:Explainable ML, non-parametric statistical learning, principled model selection, and hyperparameter tuning.
• Causal Inference:Causal model selection and identification, treatment-effect estimation, instrumental variables, and counterfactual / what-if analysis.
• Production Cloud Deployment:Implementation of mathematical and statistical models in scalable, production-grade Cloud environments.
• AI Agent Development:Design and implementation of autonomous agentic systems and multi-agent workflows using frameworks such as LangGraph, Google ADK, or AWS Bedrock AgentCore, including orchestration, state/context management, tool integration, and safe execution.

Salary Range The expected base salary for this New York, NY, United States-based position is $115000-$180000. 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 availableto active, non-temporary, full-time and part-time US employees who work at least 20 hours per week, can be found here .

Healthcare & Medical Services

We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally

We offer competitive vacation policies based on employee level and office location. We promote time off from work to recharge by providing generous vacation entitlements and a minimum of three weeks expected vacation usage each year.

Financial Wellness & Retirement

We assist employees in saving and planning for retirement, offer financial support for higher education, and provide a number of benefits to help employees prepare for the unexpected. We offer live financial education and content on a variety of topics to address the spectrum of employees’ priorities.

Health

We offer a medical advocacy service for employees and family members facing critical health situations, and counseling and referral services through the Employee Assistance Program (EAP). We provide Global Medical, Security and Travel Assistance and a Workplace Ergonomics Program. We also offer state-of-the-art on-site health centers in certain offices.

Fitness

To encourage employees to live a healthy and active lifestyle, some of our offices feature on-site fitness centers. For eligible employees we typically reimburse fees paid for a fitness club membership or activity (up to a pre-approved amount).

We offer on-site child care centers that provide full-time and emergency back-up care, as well as mother and baby rooms and homework rooms. In every office, we provide advice and counseling services, expectant parent resources and transitional programs for parents returning from parental leave. Adoption, surrogacy, egg donation and egg retrieval stipends are also available.

Benefits at Goldman Sachs

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