ZipRecruiter

Log In

2

Entry Level Quant Developer Jobs in New York (NOW HIRING)

Precise - Int

Entry-Level Financial Analyst

New York, NY · On-site

... Engineering, and Legal firms, in search of entry-level financial analysts for our rapidly growing ... Responsibilities • Mapping and analyzing quantitative data • Preparing management reports • ...

PDT Partners

Quantitative Researcher

New York, NY · On-site

$190K - $250K/yr

Experience Required: Entry-level (PhD Program) or Experienced (Postdoc, Faculty, Scientific Lab ... PhD in Math, Science, Engineering and other relevant disciplines The PDT team - a quantitative ...

IBM

Data Engineer Intern 2027

New York, NY · On-site

... entry-level positions. You'll receive a status update email for each application, so be sure to ... Currently pursuing a quantitative degree in Computer Science, Statistics, Mathematics, Engineering ...

New

IBM

Data Engineer Intern 2027

New York, NY

... entry-level positions. You'll receive a status update email for each application, so be sure to ... Currently pursuing a quantitative degree in Computer Science, Statistics, Mathematics, Engineering ...

New

IBM

Data Engineer Intern 2027

Bronx, NY · On-site

... entry-level positions. You'll receive a status update email for each application, so be sure to ... Currently pursuing a quantitative degree in Computer Science, Statistics, Mathematics, Engineering ...

New

next page

Showing results 1-20

All JobsQuant Developer JobsEntry Level Quant Developer JobsEntry Level Quant Developer Jobs in New York

Entry Level Quant Developer information

What are the key skills and qualifications needed to thrive as an entry level quant developer?

To thrive as an Entry Level Quant Developer, you need strong quantitative skills, programming proficiency (such as Python, C++, or Java), and a background in mathematics, statistics, or a related field. Familiarity with financial modeling tools, statistical analysis software, and version control systems like Git is often required. Analytical thinking, attention to detail, and effective communication are crucial soft skills for collaborating with teams and translating complex data into actionable insights. These skills and qualities are essential for developing robust quantitative models and supporting data-driven decision-making in fast-paced financial environments.

What is the difference between Entry Level Quant Developer vs Quant Analyst?

AspectEntry Level Quant DeveloperQuant Analyst
Required CredentialsBachelor's in Math, CS, or Finance; programming skillsBachelor's or Master's in Finance, Economics, or Math; strong analytical skills
Work EnvironmentFinancial firms, hedge funds, trading desks; coding-focusedFinancial institutions, asset management; analysis and modeling
Employer & Industry UsageCommon in trading firms, hedge funds, investment banksPrevalent in asset management, hedge funds, banks

While both roles involve quantitative skills, Entry Level Quant Developers focus on coding and implementing trading algorithms, whereas Quant Analysts primarily analyze data and develop financial models. The roles often overlap but differ mainly in their core responsibilities and daily tasks.

What are some typical challenges faced by entry level quant developers when transitioning from academia to a professional finance environment?

Entry level quant developers often find the transition from academic settings to professional finance environments challenging due to the fast-paced nature of the industry and the need for effective collaboration with traders, analysts, and senior developers. In addition to applying their quantitative and programming skills, new hires must quickly adapt to production-level coding standards, version control systems, and the need for rigorous code reviews. Time-sensitive problem-solving and balancing multiple projects are common, making communication and prioritization essential skills. Proactively seeking mentorship and being open to feedback can significantly ease this transition and foster professional growth.

What is an entry level quant developer?

Entry level quant developers are professionals who use mathematical models, programming, and data analysis to help financial institutions make trading decisions or manage risk. They typically work with large datasets and implement algorithms in programming languages like Python, C++, or Java. While entry level roles may focus more on coding and supporting senior quants, they provide a strong foundation in both finance and technology. These roles often require strong analytical skills, basic financial knowledge, and proficiency in at least one programming language.

What are the most commonly searched types of Quant Developer jobs in New York?

The most popular types of Quant Developer jobs in New York are:

What are popular job titles related to Entry Level Quant Developer jobs in New York?

For Entry Level Quant Developer jobs in New York, the most frequently searched job titles are:

What job categories do people searching Entry Level Quant Developer jobs in New York look for?

The top searched job categories for Entry Level Quant Developer jobs in New York are:

What cities in New York are hiring for Entry Level Quant Developer jobs?

Cities in New York with the most Entry Level Quant Developer job openings:

Entry Level Quant Developer jobs near you
Infographic showing various Entry Level Quant Developer job openings in New York as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.

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

Goldman Sachs & Co.

Manhattan, NY • On-site

Other

Posted 18 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 entry level candidates 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

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Goldman Sachs logo

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

View All Goldman Sachs Jobs

Apply