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How much do part time quant trading jobs pay per year?

As of Jun 28, 2026, the average yearly pay for part time quant trading 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.

How much does a quant trader make per hour?

A part-time quant trader's hourly earnings vary widely based on experience, performance, and the firm's size, but they typically earn between $50 and $150 per hour. Many quant traders are paid a combination of salary and performance-based bonuses, and success often depends on strong quantitative skills and programming knowledge.

What jobs make $1,000,000 a year?

In the field of quantitative trading, highly successful traders or hedge fund managers can earn over $1 million annually through profit sharing, bonuses, and management fees. These roles typically require advanced skills in mathematics, programming, and finance, along with significant experience and capital under management.

What job makes $10,000 a month without a degree?

Part time quantitative trading can generate $10,000 or more per month for skilled traders who have strong analytical abilities, knowledge of financial markets, and proficiency with trading algorithms and tools. Success typically depends on experience, strategy, and risk management, rather than formal education alone.

What is part time quant trading?

Part time quant trading refers to using quantitative methods, such as statistical analysis and mathematical models, to trade financial securities while working fewer hours than a full-time position. Part-time quant traders often use algorithms and data-driven strategies to make trading decisions, sometimes in addition to other work or academic commitments. This role can be performed remotely or on-site and may involve developing and testing trading models, analyzing market data, and executing trades. It is suited for individuals with strong analytical and programming skills who are looking to gain experience or supplement their income.

What are typical responsibilities and expectations for someone in a part-time quant trading position?

In a part-time quant trading role, you'll typically be tasked with analyzing large datasets, developing and backtesting trading algorithms, and monitoring the performance of existing trading strategies. You'll often work closely with full-time quantitative researchers and traders, providing support on specific projects or focusing on particular asset classes. Since the role is part-time, efficient time management and clear communication are essential, as you'll need to coordinate your contributions with the broader team and ensure your work integrates smoothly with ongoing initiatives. This position offers valuable exposure to real-world trading environments and the opportunity to enhance your technical and analytical skills.

What are the key skills and qualifications needed to thrive as a Part Time Quant Trader, and why are they important?

To thrive as a Part Time Quant Trader, you need strong quantitative skills, proficiency in programming (especially Python or R), and a solid understanding of financial markets, typically supported by a degree in mathematics, finance, or a related field. Familiarity with trading platforms, statistical analysis tools, and data visualization systems is essential, as are certifications like CFA or FRM for added credibility. Analytical thinking, attention to detail, and the ability to manage risk and work independently are standout soft skills for this role. These skills ensure effective strategy development, accurate data-driven decisions, and successful performance in the dynamic and fast-paced trading environment.

Is 30 too late to become a quant?

Becoming a quantitative trader or analyst at age 30 is feasible, as many professionals enter the field with diverse backgrounds and skills in mathematics, programming, and finance. Success often depends on acquiring relevant technical skills, such as proficiency in Python or C++, and gaining experience through internships or self-study, regardless of age.
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Part Time Quant Trading jobs near you
Infographic showing various Part Time Quant Trading job openings in the United States as of June 2026, with employment types broken down into 2% Locum Tenens, 1% Internship, 8% As Needed, 8% Full Time, 76% Contract, and 5% Nights. Highlights an 91% Physical, 4% Hybrid, and 5% Remote job distribution, with an average salary of $169,729 per year, or $81.6 per hour.
Research and Product Development PhD Student Intern (Part-Time, 12-Month Program)

Research and Product Development PhD Student Intern (Part-Time, 12-Month Program)

CME Group

New York, NY • On-site

Part-time

Medical

Posted 7 days ago

Job description

CME Group is the world's leading derivatives marketplace - but our fastest-growing frontier is data and analytics. With trillions in notional trading across our markets, CME produces one of the richest financial datasets on the planet: full-depth order books, microstructure signals, volatility surfaces, curve dynamics, order flow distributions, term-structure shifts, and real-time global risk transfer behavior.
Through our strategic partnership with Google Cloud Platform (GCP), we now have unmatched compute power to analyze this data at scale and build the next generation of analytics, financial mathematical models, and AI systems.
This internship gives you direct access to that ecosystem.
About the Role
We are seeking a PhD student-level intern (20 hours/week, part-time, 1-2 days onsite in New York) for a 12-month appointment working directly with the Executive Director leading CME's Data & Analytics buildout. This is a ground-floor opportunity to contribute to both the modernization of CME's core analytics and the development of new AI-driven, mathematically rigorous models.
The role has three interlocking pillars:
1. Rebuilding & Operationalizing CME's Financial Mathematical Models
CME has a deep library of proprietary models across asset classes - some long-standing and widely used, others emerging. You will help:
  • Review and where appropriate suggest improvements to analytical models using modern numerical and statistical methods
  • Document and validate models in alignment with governance and regulatory standards
  • Work with technology to prepare models for deployment using GCP infrastructure
  • Help to document and at times direct conversion of legacy codebases into robust, maintainable analytics libraries
  • Ensure mathematical transparency, reproducibility, and version control
  • Collaborate with Product, Clearing, Data Science, Index, and Engineering teams

Examples of model domains include:
  • Curve construction & interpolation
  • Volatility modelling (e.g., SABR in depth, SVI, spline surfaces, curve fitting)
  • Option pricing & Greeks (finite-difference / Monte Carlo)
  • Microstructure analytics (order book modeling, liquidity metrics)
  • Risk models (scenario generation, historical VaR, CVaR, distribution modelling)
  • Statistical estimation for high-frequency data

Pros:
  • Rare exposure to enterprise-scale quant model development
  • Hands-on work with real market datasets, not simulated data
  • Opportunity to improve models used by global financial institutions

Cons:
  • High expectations for precision, mathematical clarity, and documentation
  • Requires comfort with governance and validation standards

2. Building New Machine Learning, Embedding, and Agent-Based Models
You will help shape the next generation of CME's AI capabilities, including:
  • ML models trained on massive historical market datasets
  • Embedding models for numerical, textual, and transactional data
  • Agent-based systems and agent-communication protocols
  • Market microstructure simulations powered by intelligent agents
  • Predictive analytics and anomaly detection frameworks
  • Hybrid models combining financial mathematics with ML architectures

This work sits at the intersection of quant research and state-of-the-art AI - and will be developed directly on GCP, leveraging tools such as BigQuery, Vertex AI, and large-scale notebooks.
Pros:
  • Frontier-level ML exposure with real, large datasets
  • Creative freedom on prototypes
  • Real influence on CME's long-term AI strategy

Cons:
  • Ambiguity: some initiatives start from a blank page
  • Must be comfortable iterating quickly and defending methodological choices

3. Quant Research, Data Engineering, and Cross-Functional Collaboration
You will also:
  • Conduct quantitative research across CME's datasets
  • Build analytical pipelines using Python + GCP tooling
  • Develop visualizations and explainers for internal and client use
  • Support monthly and quarterly research themes
  • Present written and verbal findings to senior leadership
  • Help shape best practices for model governance, testing, and production readiness

What You Bring
Required
  • PhD candidate in mathematics, statistics, physics, engineering, computer science, quantitative finance, econometrics, or a related field
  • Strong foundation in financial mathematics (stochastic calculus, derivatives modeling, numerical methods, or equivalent)
  • Proficiency in Python and scientific computing libraries
  • Ability to communicate complex concepts clearly in writing
  • Strong analytical discipline and attention to detail
  • Self-starter comfortable working across multiple business lines

Bonus
  • Experience with GCP: BigQuery, Vertex AI, Dataflow, C++
  • Experience with ML, embeddings, or agent-based systems
  • Background in market microstructure, derivatives, or high-frequency data
  • Prior publications, technical reports, or model documentation

Schedule & Structure
  • 20 hours/week
  • 1-2 days onsite
  • 12-month internship
  • Flexible to accommodate academic commitments
  • Direct mentorship and collaboration with an Executive Director leading CME's new Data & Analytics function

This is not a typical internship - you will be a core contributor to a strategic buildout.
Why This Is a Rare Opportunity for a PhD Candidate
  • Access to one of the deepest financial datasets in existence
  • Ability to work on both quantitative financial models and cutting-edge AI systems
  • Experience bringing models into enterprise-scale production
  • Direct contribution to CME's next-generation data analytics platform
  • Exposure to real governance, validation, and model-risk frameworks
  • A signature line on your CV that signals:
    "I built models used by global markets."

#EarlyCareers
CME Group is committed to offering a competitive pay package for our employee interns. The pay range typically applicable to our intern roles is $23.84--$39.71. Actual pay offered will be dependent on a wide array of factors including but not limited to: relevant experience, skills, education, location of the internship, and the internship area of focus. Through our benefits program, we offer our employee interns the opportunity to participate in select offerings. This includes our comprehensive health coverage and a mental health benefit.
CME Group: Where Futures are Made
CME Group is the world's leading derivatives marketplace. But who we are goes deeper than that. Here, you can impact markets worldwide. Transform industries. And build a career by shaping tomorrow. We invest in your success and you own it - all while working alongside a team of leading experts who inspire you in ways big and small. Problem solvers, difference makers, trailblazers. Those are our people. And we're looking for more.
At CME Group, we embrace our employees' unique experiences and skills to ensure that everyone's perspectives are acknowledged and valued. As an equal-opportunity employer, we consider all potential employees without regard to any protected characteristic.
Important Notice: Recruitment fraud is on the rise, with scammers using misleading promises of job offers and interviews to solicit money and personal information from job seekers. CME Group adheres to established procedures designed to maintain trust, confidence and security throughout our recruitment process. Learn more here.
CME Group logo

About CME Group

Sourced by ZipRecruiter

As the world’s leading derivatives marketplace, CME Group is where the world comes to manage risk. We enable clients to trade futures, options, cash and OTC markets, optimize portfolios, and analyze data – empowering market participants worldwide to efficiently manage risk and capture opportunities. CME Group exchanges offer the widest range of global benchmark products across all major asset classes based on interest rates, equity indexes, foreign exchange, energy, agricultural products and metals. We meet uncertainty and volatility with confidence and clarity, across the trading lifecycle and around the world.

Industry

Finance and insurance

Company size

1,001 - 5,000 Employees

Headquarters location

Chicago, IL, US

Year founded

2007

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