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Corporate Planning & Management-New York-Senior Analyst-Quantitative Engineering

Job in New York, New York County, New York, 10261, USA
Listing for: Goldman Sachs
Full Time position
Listed on 2026-08-02
Job specializations:
  • IT/Tech
    Data Scientist
  • Finance & Banking
    Data Scientist
Salary/Wage Range or Industry Benchmark: 110000 - 130000 USD Yearly USD 110000.00 130000.00 YEAR
Job Description & How to Apply Below
Location: New York

Role Overview

As an Sr. Analyst Quantitative Strategist (Strat) within the CPM Strats team, you will focus on the design, development, and implementation of quantitative models to drive Budget Planning & Management
. In this role, you will model and forecast revenues, expenses, and balance sheet dynamics. You will deploy scalable solutions on AWS Cloud and build secondary but core AI/agentic capabilities to streamline financial planning and analysis, with opportunities to leverage Rust to accelerate scientific computing.

This position is at the Analyst level and is highly suited for recent graduates looking to apply advanced mathematical, statistical, and computational techniques to real-world corporate planning and financial forecasting challenges, and develop expertise developing 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 explainable Machine Learning (ML) models for financial event prediction, revenue forecasting, and expense projection. 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 AWS 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, 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.

  • Develop, implement, and document scenarios comprised of a broad range of economic and financial variables for budget planning and management within the Firm.

  • Collaborate with internal stakeholders, analyzing user needs from a scenario design perspective and addressing data, model, and implementation issues.

  • Analyze large datasets (structured and unstructured) to build predictive models of business-relevant financial variables (revenues, expenses, and balance sheet).

  • Develop, refine, and improve scenarios by leveraging knowledge in financial markets, economics, current events, statistical analysis, and programming.

  • Build and challenge revenue and expense models, identifying and quantifying vulnerabilities across financial planning and forecasting.

  • Create and maintain clear and complete technical documentation of the model performance testing approach and process.

Minimum Education & Experience Requirements
  • PhD degree (U.S. or foreign equivalent) in Statistics, Computer Science, Applied Mathematics, Physics or a related quantitative field.
    No prior professional work experience is required.

  • OR

  • Master’s degree (U.S. or foreign equivalent) in Statistics, Computer Science, Applied Mathematics, Physics or a related quantitative field, and one (1) year of experience in the job offered or a related quantitative engineering role.

  • OR

  • Bachelor’s degree (U.S. or foreign equivalent) Statistics, Computer Science, Applied Mathematics, Physics or a related quantitative field, and three (3) years of experience in the job offered or a related quantitative engineering role.

PhD graduates with…

Position Requirements
10+ Years work experience
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