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Rust Quant Jobs in New York (NOW HIRING)

LHi Group Ltd

Senior Protocol Engineer

Manhattan, NY · On-site

$115K - $158K/yr

The company has recently expanded into quantitative trading after successfully building ... Design and build high-performance trading infrastructure in Rust. * Integrate with centralized and ...

New

Lawrence Harvey

Senior Protocol Engineer

New York, NY · On-site

$150K - $300K/yr

The company has recently expanded into quantitative trading after successfully building ... Design and build high-performance trading infrastructure in Rust. * Integrate with centralized and ...

New

Sei

Monaco Trading - Lead Quantitative Developer

New York, NY · On-site

$64.50 - $84.50/hr

Who You Are * 6+ years of experience across systematic trading and/or quant-dev roles, ideally ... Must be proficient in Rust * High agency individual that is able to ideate and execute, while ...

The Cypress Group

Lead Data Engineer

New York, NY · Remote

$200K - $250K/yr

Experience with Rust , or a strong interest in learning it. * Background in financial services, fintech, investment platforms, or quantitative analytics. * Experience working with large-scale ...

Keyrock

Head of Engineering - Options

New York, NY · On-site +1

We're an initiator. We have been pioneers in adopting the Rust Development language for our ... Partner closely with trading, quant, product, risk, and infrastructure stakeholders * Balance ...

Keyrock

Engineering Lead- Options

New York, NY · On-site +1

$112K - $147K/yr

We're an initiator. We have been pioneers in adopting the Rust Development language for our ... Partner closely with trading, quant, product, risk, and infrastructure stakeholders * Balance ...

Keyrock

Head of Engineering - Options

New York, NY · Remote

We're an initiator. We have been pioneers in adopting the Rust Development language for our ... Partner closely with trading, quant, product, risk, and infrastructure stakeholders * Balance ...

Keyrock

Engineering Lead- Options

New York, NY · Remote

$104K - $138K/yr

We're an initiator. We have been pioneers in adopting the Rust Development language for our ... Partner closely with trading, quant, product, risk, and infrastructure stakeholders * Balance ...

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Showing results 21-40

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Rust Quant information

What is a Rust quant?

A Rust Quant is a quantitative analyst or developer who specializes in using the Rust programming language to build financial models, trading algorithms, or risk management systems. Rust is valued in quantitative finance for its high performance, memory safety, and concurrency support, making it suitable for processing large volumes of financial data. Rust Quants typically work in hedge funds, investment banks, or fintech companies, where they design and implement efficient, reliable software to support trading and analytics. Their work often involves collaborating with data scientists, traders, and other engineers.

How does a Rust quant typically collaborate with other teams within a financial institution?

A Rust Quant often works closely with traders, data engineers, and risk analysts to develop and optimize quantitative models and trading algorithms. Collaboration involves translating financial strategies into efficient, production-ready Rust code, and ensuring that the models integrate seamlessly with existing systems. Regular communication is essential to clarify requirements, troubleshoot issues, and continuously improve performance. This cross-functional teamwork provides valuable exposure to different aspects of quantitative finance and fosters professional growth.

What are the key skills and qualifications needed to thrive as a Rust quant, and why are they important?

To thrive as a Rust Quant, you need a strong background in quantitative finance, advanced mathematics, and proficiency in the Rust programming language, often supported by degrees in math, physics, or computer science. Experience with statistical modeling libraries, version control systems like Git, and knowledge of financial data APIs are typically required. Analytical thinking, problem-solving abilities, and effective communication set top candidates apart in this role. These skills are crucial for developing reliable, high-performance trading algorithms and collaborating with interdisciplinary teams in fast-paced financial environments.

What is the difference between Rust Quant vs Quant Analyst?

AspectRust QuantQuant Analyst
Required CredentialsStrong programming skills, often with C++, Python, and Rust; advanced degrees in math, finance, or computer scienceDegree in finance, economics, or mathematics; certifications like CFA or FRM are common
Work EnvironmentTypically in tech-driven finance firms, hedge funds, or proprietary trading firms; focus on coding and model developmentUsually in investment banks, asset management firms, or hedge funds; focus on market analysis and strategy
Employer & Industry UsageUsed in quantitative trading, risk management, and algorithm developmentUsed in investment analysis, portfolio management, and risk assessment

Rust Quants focus on developing and implementing trading algorithms using programming skills, especially in Rust and related languages. Quant Analysts often analyze markets and develop financial models, with less emphasis on coding. While both roles require strong quantitative skills, Rust Quants are more technical and programming-oriented, whereas Quant Analysts focus more on financial analysis and strategy.

What are popular job titles related to Rust Quant jobs in New York? For Rust Quant jobs in New York, the most frequently searched job titles are:
What job categories do people searching Rust Quant jobs in New York look for? The top searched job categories for Rust Quant jobs in New York are:
What cities in New York are hiring for Rust Quant jobs? Cities in New York with the most Rust Quant job openings:
Rust Quant jobs near you
Infographic showing various Rust Quant job openings in New York as of August 2026, with employment types broken down into 2% Internship, 96% Full Time, and 2% Contract. Highlights an 82% In-person, and 18% Remote job distribution.

Associate, Quantitative Strategist, Core Planning and Analysis Strats

Goldman Sachs, Inc.

New York, NY • On-site

Full-time

Re-posted 16 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 170 rated banks

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.

What Goldman Sachs employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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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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