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Ai Quant Jobs (NOW HIRING)

Quant Research

New York, NY · On-site

$150K - $250K/yr

... tech, AI, culture and more. We believe prediction markets have the potential to be the largest ... We're hiring a Quant Researcher who will help build what comes next: new indices, new models, and ...

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Director, STP Desk Quant

Manhattan, NY · Hybrid

$210K - $300K/yr

The GE Quantitative Analytics team is looking for an experienced STP desk quant to help scaling up ... ML & AI: experiences in machine-learning techniques and AI. What's in it for you? We thrive on the ...

VP - GenAI Quant Developer

New York, NY · On-site

$200K - $225K/yr

Generative AI / LLM & Agentic Systems (Embedded AI Initiative) * Design, prototype, and deploy LLM-powered applications for the Rates business, e.g.: * Workflow automation for pricing, risk checks ...

Role Summary The Quantitative Researcher combines advanced AI and quantitative investing techniques to enhance and support our fundamental investment process. Working alongside experienced analysts ...

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Ai Quant information

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$98K

$169.7K

$259.5K

How much do ai quant jobs pay per year?

As of Jun 21, 2026, the average yearly pay for ai quant in the United States is $169,729.00, according to ZipRecruiter salary data. Most workers in this role earn between $134,500.00 and $199,000.00 per year, depending on experience, location, and employer.

What is an AI Quant?

An AI Quant, or Artificial Intelligence Quantitative Analyst, is a professional who combines expertise in quantitative finance and machine learning to develop advanced trading strategies, risk models, or analytics tools. AI Quants use algorithms, statistical models, and large datasets to identify patterns, forecast market trends, and make data-driven investment decisions. They often work in hedge funds, investment banks, or proprietary trading firms, collaborating with software engineers and other quants to implement and optimize AI-driven financial models.

Is 40 too old to become an quant?

Age is not a strict barrier to becoming an AI Quant, as the role values skills in programming, mathematics, and finance, which can be developed at any age. Many professionals transition into quantitative roles later in their careers by gaining relevant certifications, such as CFA or advanced degrees, and building experience with tools like Python, R, or MATLAB.

How does an AI Quant typically collaborate with data scientists, traders, and software engineers within a financial institution?

AI Quants often work closely with data scientists to develop and refine machine learning models using financial data, ensuring models are statistically robust and actionable. They collaborate with traders to translate complex quantitative signals into trading strategies that are practical and aligned with market objectives. Additionally, AI Quants partner with software engineers to implement and optimize these models for real-time deployment, ensuring that the underlying code is scalable, efficient, and reliable. This cross-functional environment requires strong communication skills and adaptability, as priorities can shift with market movements and technological advancements.

What are the key skills and qualifications needed to thrive as an AI Quant, and why are they important?

To thrive as an AI Quant, you need a strong background in quantitative analysis, mathematics, statistics, and machine learning, often supported by an advanced degree in a quantitative field. Proficiency in programming languages like Python or C++, experience with data analysis libraries (such as NumPy, pandas, and TensorFlow), and familiarity with financial modeling tools are typically required. Strong problem-solving skills, attention to detail, and effective communication set top performers apart in this role. These skills are crucial for developing robust AI-driven trading strategies and ensuring accurate, data-driven decision-making in the fast-paced financial sector.

What is the difference between Ai Quant vs Data Scientist?

AspectAi QuantData Scientist
Required CredentialsAdvanced degrees in quantitative fields, certifications in machine learning or AIDegrees in computer science, statistics, or related fields; certifications vary
Work EnvironmentFinancial firms, hedge funds, or trading firms focusing on quantitative analysisTech companies, research labs, or any industry leveraging data analysis
Employer & Industry UsagePrimarily finance and trading industriesBroad across tech, healthcare, retail, and more
Common Search & Comparison IntentUnderstanding specialized quantitative roles in financeExploring data analysis careers across industries

Ai Quants focus on developing algorithms and models for financial markets, often requiring advanced quantitative skills and finance-specific knowledge. Data Scientists have a broader scope, applying statistical and machine learning techniques across various industries. While both roles involve data analysis and programming, Ai Quants are specialized in finance, whereas Data Scientists work in diverse sectors.

Do quants make 7 figures?

Quantitative analysts, or quants, working in finance or hedge funds can sometimes earn seven-figure salaries, especially at senior levels or in high-paying firms. However, such compensation is typically reserved for experienced professionals with specialized skills in mathematics, programming, and finance, and is not the norm for all quants.

Which 3 jobs will survive AI?

AI Quant roles in finance are likely to persist because they require specialized quantitative skills, understanding of financial markets, and the ability to interpret complex data. Jobs that involve creative thinking, emotional intelligence, and complex problem-solving, such as healthcare professionals, educators, and skilled trades, are also expected to remain resilient to automation. These roles often require human judgment and adaptability that AI cannot fully replicate.

What is a $900,000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior AI researcher, machine learning director, or AI executive, often requiring advanced skills in data science, programming, and domain expertise. These roles usually involve leadership, strategic planning, and significant experience, and they may be found in large tech companies or finance firms offering competitive compensation packages.
More about Ai Quant jobs
What cities are hiring for Ai Quant jobs? Cities with the most Ai Quant job openings:
What states have the most Ai Quant jobs? States with the most job openings for Ai Quant jobs include:
Infographic showing various Ai Quant job openings in the United States as of June 2026, with employment types broken down into 100% Full Time. Highlights an 50% In-person, and 50% Remote job distribution, with an average salary of $169,729 per year, or $81.6 per hour.

Principal Quant Developer (MLOps)

Fidelity Investments

Boston, MA • On-site

$107K - $216K/yr

Other

Medical, Retirement, PTO

Posted 18 days ago


Fidelity Investments rating

8.7

Company rating: 8.7 out of 10

Based on 264 frontline employees who took The Breakroom Quiz

14th of 138 rated financial services


Job description

Job Description:

Principal Quant Developer

The Role

The Quantitative Research & Investing Technology (QRIT) team within Fidelity's Asset Management Technology group is seeking a highly motivated and curious Principal Quantitative Developer. In this role you will contribute to a dynamic and fast-paced development team supporting researchers in prototyping and delivering new systematic investment strategies. You will provide high impact solutions on various projects including alpha research, portfolio construction, and risk management. Your technology knowledge covers a broad spectrum of technologies, including R, Python, and PL/SQL databases, positioning you as a full-stack software engineer who capitalizes on enterprise technology. You are committed to constructing high-quality, scalable, robust, resilient and efficient analytical and software solutions that propel investment processes forward.

You will possess:

  • A Bachelor's degree in Computer Science, Financial Engineering, Information Technology, Information Systems, Mathematics, Physics, Statistics, Engineering, or a closely related field and six (6) years of experience as a Senior Quant Developer or similar role.
  • Alternatively, a Master's degree (or equivalent foreign education) in the same fields, accompanied by four (4) years of experience as a Lead Quantitative Development or similar role.
  • This experience should include building high-quality, robust, and efficient systems and solutions for financial investment decisions, utilizing R, Python, PL/SQL databases, and quantitative techniques.

The Expertise and Skills You Bring

Core Engineering

  • Expert in Python with experience across the development stack (full stack)
  • Exposure to object-oriented programming (OOP) and design patterns
  • Experience in at least one unit testing framework and understanding of test-driven development (TDD) concepts and methodologies
  • A commitment to writing clean, maintainable, and efficient code, with best practices for long-term maintainability

Data & Infrastructure

  • Skilled in a range of database technologies: SQL (Oracle & Snowflake), NoSQL, Graph
  • Skilled in batch and API technologies: such as batch scheduling (using Autosys and Airflow) and creating REST APIs (using FAST API and Flask)
  • Proven ability to construct and manage robust data pipelines and event-driven workflows
  • Proven expertise in system design and cloud architecture on AWS, leveraging resources including Lambda, S3, EKS, and EC2


DevOps & CI/CD

  • Experience in containerization with Docker and orchestration with Kubernetes
  • Implement CI/CD pipelines (using Linux and Jenkins), code versioning using GitHub
  • Experience in Infrastructure as Code methodologies for consistent and scalable infrastructure management


MLOps & AI Infrastructure

  • Experience operationalizing machine learning models on AWS, including services such as SageMaker (training, deployment, model registry, monitoring) and Bedrock (foundation model access and fine-tuning)
  • Operationalizing AI/ML pipelines using modern MLOps principles, including production lifecycle management of AI models
  • Familiarity with experiment tracking and model versioning tools (e.g., MLflow)
  • Identifying and deploying applied ML solutions relevant to quantitative investing: time series forecasting, anomaly detection, NLP, and predictive analytics
  • Awareness of responsible AI governance practices
  • Demonstrated enthusiasm for contributing to all facets of our AI ecosystem, from application development to MLOps/LLMOps infrastructure, with a versatile, full-stack engineering mindset


Quantitative & Domain Knowledge

  • Demonstrated knowledge of mathematics, statistics, and quantitative finance
  • Deep understanding of quantitative techniques and methods, statistics and econometrics including probability, linear regression and time series data analysis
  • Analyze and design systems to implement quantitative models for systematic financial investments using R and Python, including time series forecasting models, multi-asset class portfolio construction strategies, risk management tools, alpha research, and simulation-based algorithms
  • Domain knowledge in either equities, fixed income or alternative asset classes
  • Progress towards CFA (or equivalent) a plus

Collaboration & Communication

  • Strong presentation and communication skills, with a knack for engaging with quant researchers and investment professionals
  • Strong problem-solving skills, with a proven ability to work effectively in cross-functional teams
  • A creative problem solver and a curiosity fueled by keeping up with advanced methodologies and industry trends, especially in the finance community
  • Lead the implementation of a research project through the entire software development lifecycle using a full-stack implementation
  • Assist Research teams in developing new models and products that will provide an advantage to the organization in the marketplace
  • Demonstrates eagerness and aptitude for rapidly adopting new frameworks, technologies, and best practices

The Team

The Quant Development team is part of Asset Management's Quantitative Research & Investment Technology group. We partner with Asset Management's Advance Strategies and Research team on cutting edge projects including systematic investment strategies, portfolio construction, risk management, alpha research, and GenAI. We build high quality, robust, and highly-scalable solutions that are used to improve Asset Management's efficiency and decision-making processes.

The base salary range for this position is $107,000-216,000 USD per year.

Placement in the range will vary based on job responsibilities and scope, geographic location, candidate’s relevant experience, and other factors.

Base salary is only part of the total compensation package. Depending on the position and eligibility requirements, the offer package may also include bonus or other variable compensation.

We offer a wide range of benefits to meet your evolving needs and help you live your best life at work and at home. These benefits include comprehensive health care coverage and emotional well-being support, market-leading retirement, generous paid time off and parental leave, charitable giving employee match program, and educational assistance including student loan repayment, tuition reimbursement, and learning resources to develop your career. Note, the application window closes when the position is filled or unposted.

Please be advised that Fidelity’s business is governed by the provisions of the Securities Exchange Act of 1934, the Investment Advisers Act of 1940, the Investment Company Act of 1940, ERISA, numerous state laws governing securities, investment and retirement-related financial activities and the rules and regulations of numerous self-regulatory organizations, including FINRA, among others. Those laws and regulations may restrict Fidelity from hiring and/or associating with individuals with certain Criminal Histories.

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