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After School Quant Trading Jobs (NOW HIRING)

Deeter Analytics Inc

Quant Trading

$300K/yr

After years of discretionary success, we think we have some unique ways of seeing the market and ... We're launching a dedicated algorithmic division-and we're looking for a Head of Quant Trading to ...

Virtu Financial

$5.0K - $5.8K/wk

Quant Trading Internship Virtu's internship program offers students an extraordinary opportunity to ... Team player: authentic, genuine person who is capable of working collective goals After applicants ...

Virtu Financial

Internship - Quantitative Trading

Austin, TX · On-site

$5.0K - $5.8K/wk

Quant Trading Internship Virtu's internship program offers students an extraordinary opportunity to ... Team player: authentic, genuine person who is capable of working collective goals After applicants ...

Virtu Financial

Quantitative Trader

Chicago, IL

$150K - $200K/yr

... trading solutions to our clients. As a market maker, Virtu provides deep liquidity that helps to ... THE PROCESS After applicants pass an initial resume screening, an online test will be sent via ...

Da Vinci

Experienced Quant

Miami, FL · On-site

As a Quant Trader * Generate profits, trading by position taking and market making * Manage and ... Social events and after-work drinks

Virtu Financial

Quantitative Trader

Chicago, IL · On-site

$150K - $200K/yr

... trading solutions to our clients. As a market maker, Virtu provides deep liquidity that helps to ... THE PROCESS After applicants pass an initial resume screening, an online test will be sent via ...

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After School Quant Trading information

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$98K

$169.7K

$259.5K

How much do after school quant trading jobs pay per year?

As of Jul 28, 2026, the average yearly pay for after school 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.

Can you get into quant after graduating?

Yes, many quantitative trading firms hire graduates with strong backgrounds in mathematics, computer science, or engineering. Entry often requires programming skills, knowledge of financial markets, and relevant internships or research experience. A solid understanding of statistical analysis and experience with tools like Python or R can improve chances of entering the field.

What is an After School Quant Trading job?

An After School Quant Trading job typically refers to a part-time or internship position where students, often at the high school or college level, engage in quantitative trading activities after regular school hours. These roles involve using mathematical models, statistical analysis, and computer programming to make financial trading decisions. It is designed to help students gain hands-on experience in the world of quantitative finance and trading, often under the mentorship of industry professionals. Responsibilities may include analyzing market data, developing trading algorithms, and learning about risk management strategies. These positions are a great opportunity for students interested in finance, math, or computer science to explore the field and build relevant skills.

Does JP Morgan hire quants?

JP Morgan hires quantitative analysts, often called quants, for roles in trading, risk management, and technology. These positions typically require strong skills in mathematics, programming, and financial modeling, and may involve working with tools like Python, C++, or MATLAB. Quant roles at JP Morgan are competitive and often require relevant experience or advanced degrees in related fields.

What is the difference between After School Quant Trading vs Quantitative Analyst?

AspectAfter School Quant TradingQuantitative Analyst
Required CredentialsTypically a background in mathematics, finance, or computer science; often an internship or part-time experienceAdvanced degrees (Master's or PhD) in quantitative fields; strong programming and statistical skills
Work EnvironmentPart-time, flexible hours, often in a trading firm or hedge fund settingFull-time, office-based, in financial institutions or investment firms
Employer & Industry UsageUsed by trading firms, hedge funds, and financial startups for early talent developmentEmployed across banks, hedge funds, asset managers, and financial consultancies for strategy development

While both roles involve quantitative skills and finance knowledge, After School Quant Trading is typically a part-time, entry-level position focused on gaining practical trading experience, whereas a Quantitative Analyst is a full-time role requiring advanced education and involved in developing complex models for investment strategies.

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

To thrive as an After School Quant Trader, you need strong quantitative and analytical skills, a solid understanding of financial markets, and proficiency in mathematics or statistics, often supported by coursework or certifications in finance or related fields. Familiarity with programming languages like Python or R, experience with trading platforms, and knowledge of data analysis tools are typically required. Critical thinking, attention to detail, and the ability to work independently are valuable soft skills in this role. These skills ensure effective strategy development, risk management, and successful execution of trades in a competitive, data-driven environment.

Is 40 too old to become a quant?

Age is not a strict barrier to becoming an quantitative trader, as success depends more on skills, knowledge, and experience in mathematics, programming, and finance. Many quants transition into the field later in their careers, often leveraging prior experience in related areas such as data analysis or software development. Continuous learning and proficiency with tools like Python, R, or MATLAB are important regardless of age.

What are some common challenges faced by after-school quant trading professionals, and how can they be addressed?

After-school quant trading professionals often face the challenge of balancing their trading activities with academic or other daytime commitments. This can make time management and maintaining discipline crucial, especially when monitoring markets or backtesting strategies in limited hours. Additionally, staying updated with rapidly evolving quantitative methods and technology can be demanding. Joining online communities, leveraging automation tools, and prioritizing tasks can help overcome these challenges and enhance productivity in the role.
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After School Quant Trading jobs near you
Infographic showing various After School Quant Trading job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution, with an average salary of $169,729 per year, or $81.6 per hour.

Quant Trading

Deeter Analytics Inc

Remote

$300K/yr

Full-time

Posted 6 days ago

Job description

About Deeter Investments
Deeter Investments is a founder‑led proprietary well funded trading firm built around real‑time, data‑driven decision‑making. We prize curiosity, collaboration, and a bias for action. After years of discretionary success, we think we have some unique ways of seeing the market and developing alpha for the future that have high odds of success. We're launching a dedicated algorithmic division-and we're looking for a Head of Quant Trading to architect and scale this effort from day one. Role Summary
You will spearhead the development, optimization, and deployment of cutting‑edge algorithmic strategies and quantitative models. The position blends deep hands‑on technical work with high‑level strategic oversight across research, engineering, and trading operations.
Key Responsibilities
Quantitative Strategy Development & Research
  • Algorithm Design: Lead the creation and refinement of proprietary trading algorithms rooted in the firm's market framework, leveraging advanced statistical and machine‑learning techniques.
  • Modeling & Simulation: Build forecasting, signal‑generation, and risk models; run rigorous back‑tests and simulations to validate performance.
  • Data Analysis: Mine large, heterogeneous datasets (market microstructure, alternative data, etc.) for actionable insights.
  • Innovation: Continuously evaluate emerging research (deep learning, reinforcement learning, agent‑based modeling) to sharpen our edge.

Technical Infrastructure & Implementation
  • System Architecture: Partner with engineering to design high‑throughput trading systems that scale globally.
  • Software Development: Oversee codebases in Python, and C++; enforce best practices for testing, CI/CD, and performance monitoring.
  • Automation & Integration: Build end‑to‑end pipelines for data ingestion, model training, and live deployment; ensure seamless connection to execution venues and data feeds.
  • Tech‑Stack Stewardship: Select and integrate best‑in‑class analytics platforms, databases, and cloud resources.

Performance Analysis & Risk Management
  • Metrics & Analytics: Define and track KPIs-alpha decay, slippage, Sharpe, drawdown, and latency-via real‑time dashboards.
  • Risk Controls: Embed robust risk models and dynamic hedging; enforce firm‑wide limits and compliance requirements.
  • Optimization: Iterate relentlessly-parameter sweeps, sensitivity analyses, and scenario tests to future‑proof strategies.

Collaboration & Leadership
  • Team Mentorship: Grow and mentor a multidisciplinary team of quants, data scientists, and engineers; cultivate a culture of experimentation and peer review.
  • Documentation & Code Quality: Champion readable, well‑tested, version‑controlled code and transparent research notebooks.

Qualifications
  • Education: B.S. or M.S. in a quantitative field such as Mathematics, Computer Science, Engineering, Statistics, or Physics.
  • Experience: Minimum 2 years building and deploying profitable algorithmic strategies at a hedge fund, bank, or proprietary trading firm.
  • Programming: Advanced expertise in at least one core language (Python, C++, or Java) and familiarity with Linux, Git, and CI workflows.
  • Data Science: Deep knowledge of statistical modeling, and machine‑learning frameworks (PyTorch, TensorFlow, scikit‑learn).
  • Systems: Proven skill in real‑time data pipelines, distributed/cloud computing, and performance optimization.
  • Language: Fluent English (written and spoken) is required.
  • Soft Skills: Exceptional analytical rigor, clear communication, and the leadership mindset to help build a high‑performance team from scratch. Deep and careful thinking but still able to progress and iterate quickly

What we offer
-A well-funded trading firm expanding into AI research and discovery - bring your best ideas and be rewarded for them.
-Real ownership and influence on roadmap, direction and products.
-Competitive base compensation with significant upside tied to results.
-A culture optimized for deep work, fast learning, and doing the right thing.
-Unique and successful first principles based approach to markets that we haven't heard anywhere else
Compensation $400k-1m + upside exposure

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