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Entry Level Economic Forecasting Analyst Jobs in Edison, NJ

Bank of Montreal

Global Markets Analyst

New York, NY · On-site

$110K/yr

Capital Mrkts Sales & Service The Global Markets Analyst role is an entry-level position, designed ... Bachelor's degree in finance, economics, business, engineering, data science, or a related field.

Rilla

FP&A Analyst

New York, NY · On-site

$120K - $170K/yr

Run variance analysis vs. plan, forecast, and prior periods - surface trends, risks, and drivers ... Analyze unit economics and cost drivers across customers, products, and teams to support pricing ...

Bausch + Lomb

Financial Analyst I

Bridgewater, NJ · On-site

Financial Planning & Forecasting * Support the annual operating plan, forecast, and long-range ... Bachelor's degree in Finance, Accounting, Economics, or a related field required. * 2+ years of ...

Rouse Properties

Energy Trading Analyst

Manhattan, NY

$90K - $100K/yr

The Energy Trading Analyst will be responsible for price forecasting and physical bid/offer ... Bachelor's degree in engineering, economics, business, finance, information technology, or other ...

Brookfield Renewable

Energy Trading Analyst

Manhattan, NY · On-site

$90K - $100K/yr

The Energy Trading Analyst will be responsible for price forecasting and physical bid/offer ... Bachelor's degree in engineering, economics, business, finance, information technology, or other ...

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All JobsEconomic Forecasting Analyst JobsEntry Level Economic Forecasting Analyst JobsEntry Level Economic Forecasting Analyst Jobs in Edison, NJ

Entry Level Economic Forecasting Analyst information

See Edison, NJ salary details

$32.1K

$75.8K

$134.6K

How much do entry level economic forecasting analyst jobs pay per year?

As of Aug 14, 2026, the average yearly pay for entry level economic forecasting analyst in Edison, NJ is $75,844.00, according to ZipRecruiter salary data. Most workers in this role earn between $54,400.00 and $90,100.00 per year, depending on experience, location, and employer.

What is the difference between Entry Level Economic Forecasting Analyst vs Entry Level Data Analyst?

AspectEntry Level Economic Forecasting AnalystEntry Level Data Analyst
Required CredentialsBachelor's in Economics, Finance, or related field; some roles may prefer internshipsBachelor's in Statistics, Mathematics, or related field; certifications like Excel or SQL helpful
Work EnvironmentFinancial institutions, government agencies, consulting firmsTech companies, marketing firms, healthcare organizations
Industry UsageUsed for economic trend analysis, forecasting, policy advisingUsed for data collection, analysis, reporting to support business decisions

The main difference is that Entry Level Economic Forecasting Analysts focus on analyzing economic data to predict future trends, often working with macroeconomic indicators. In contrast, Entry Level Data Analysts handle a broader range of data types across various industries, focusing on interpreting data to inform operational decisions. Both roles require strong analytical skills and proficiency with data tools, but their focus and application differ significantly.

What are popular job titles related to Entry Level Economic Forecasting Analyst jobs in Edison, NJ?

For Entry Level Economic Forecasting Analyst jobs in Edison, NJ, the most frequently searched job titles are:

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What cities near Edison, NJ are hiring for Entry Level Economic Forecasting Analyst jobs?

Cities near Edison, NJ with the most Entry Level Economic Forecasting Analyst job openings:

Entry Level Economic Forecasting Analyst jobs near you
Infographic showing various Entry Level Economic Forecasting Analyst job openings in Edison, NJ as of August 2026, with employment types broken down into 91% Full Time, 8% Part Time, and 1% Contract. Highlights an 96% Physical, 2% Hybrid, and 2% Remote job distribution, with an average salary of $75,844 per year, or $36.5 per hour.

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

Goldman Sachs, Inc.

New York, NY • On-site

Full-time

Posted 17 days ago

Goldman Sachs rating

8.3

Company rating: 8.3 out of 10

Based on 27 frontline employees who took The Breakroom Quiz

47th of 171 rated banks

Job description


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 strong academic research backgrounds are highly preferred. For non-PhD candidates, we value contributions to open source projects, publications, and other contributions that provide evidence of exceptional skill.
Special Skills Required to Perform the Job
Prior experience (which can be fully satisfied through graduate-level academic research, coursework, or dissertation work for PhD candidates) must include 0 years with a PhD OR one (1) year with a Master's OR three (3) years with a Bachelor's with the following:
  • Programming Languages: Rust, Python, or C++. (Rust is utilized primarily to accelerate scientific computing and may also be leveraged for agentic workflows).
  • Econometrics & Time-Series Analysis: Modern time-series econometric techniques for forecasting, structural-break analysis, and regime-switching analysis of financial metrics.
  • Simulation and Uncertainty Quantification: Monte Carlo simulation and modern Conformal Prediction methods for uncertainty quantification in financial planning.
  • Machine Learning and Non-Parametric Statistics: Statistical learning methods with emphasis on explainable ML, causal model selection, and hyperparameter tuning.
  • Production Cloud Deployment: Implementation of mathematical and statistical models in scalable, production-grade AWS Cloud environments.
  • Data Management: Management and processing of large-scale structured and unstructured datasets using database query languages (e.g., SQL) and data management tools.
  • 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 graph-based orchestration, state and context management, tool integration, and safe execution environments.

Salary Range
The expected base salary for this New York, New York, United States-based position is $110000-$130000. 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.

What Goldman Sachs employees say

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About Goldman Sachs

Sourced by ZipRecruiter

At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world. 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, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs.

Industry

Finance and insurance

Company size

10,000+ Employees

Headquarters location

New York, NY, US

Year founded

1869

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