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Machine Learning Quant Jobs in New York (NOW HIRING)

Injective Labs

Quant Researcher

New York, NY · On-site +1

As a part of our Quant team you'll be studying the crypto market to find profitable trading ... Apply statistical and machine-learning techniques to generate, validate, and improve trading ...

Quanta Search

Delta One Quant Researcher

Manhattan, NY · On-site

Familiarity with machine learning libraries and techniques * Ability to manage multiple competing ... Team-based quantitative/automated trading experience * Knowledge of complex financial products and ...

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Machine Learning Quant information

See New York salary details

$57.4K

$130.4K

$215K

How much do machine learning quant jobs pay per year?

As of Jun 16, 2026, the average yearly pay for machine learning quant in New York is $130,371.00, according to ZipRecruiter salary data. Most workers in this role earn between $85,900.00 and $166,800.00 per year, depending on experience, location, and employer.

What is a Machine Learning Quant job?

A Machine Learning Quant is a specialist in quantitative finance who applies machine learning techniques to develop trading strategies, manage risk, and analyze financial data. They leverage statistical models, deep learning, and reinforcement learning to identify patterns in market data and optimize predictions. This role typically involves programming in Python or C++, working with large datasets, and collaborating with traders and researchers. Machine Learning Quants are employed by hedge funds, investment banks, and proprietary trading firms to gain a competitive edge in financial markets.

What are the key skills and qualifications needed to thrive in the Machine Learning Quant position, and why are they important?

To thrive as a Machine Learning Quant, you need strong skills in quantitative analysis, programming (often in Python or C++), statistical modeling, and a solid foundation in applied mathematics, typically supported by a degree in a quantitative field such as mathematics, physics, computer science, or engineering. Familiarity with machine learning frameworks (like TensorFlow or PyTorch), financial data platforms, and certifications such as CFA or advanced degrees can be advantageous. Critical thinking, collaboration, and clear communication are key soft skills that enhance effectiveness in working with both technical and non-technical stakeholders. These competencies are crucial for building and validating models that inform high-stakes financial strategies and deliver value in fast-paced trading environments.

What are typical daily responsibilities for a Machine Learning Quant in a financial firm?

As a Machine Learning Quant, your day often involves researching and developing predictive models using large financial datasets, backtesting quantitative strategies, and optimizing algorithms for speed and accuracy. You'll collaborate closely with traders, data engineers, and other quants to implement models in live trading environments and refine them based on performance feedback. Regular activities also include monitoring new data sources, adjusting to changes in the market, and documenting your methodologies for regulatory or team review. This multidisciplinary work environment offers the opportunity to continuously learn and directly impact trading outcomes.

What are the most commonly searched types of Machine Learning Quant jobs in New York? The most popular types of Machine Learning Quant jobs in New York are:
What are popular job titles related to Machine Learning Quant jobs in New York? For Machine Learning Quant jobs in New York, the most frequently searched job titles are:
What job categories do people searching Machine Learning Quant jobs in New York look for? The top searched job categories for Machine Learning Quant jobs in New York are:
Machine Learning Quant jobs near you
Infographic showing various Machine Learning Quant job openings in New York as of June 2026, with employment types broken down into 67% Full Time, and 33% Part Time. Highlights an 67% In-person, and 33% Remote job distribution, with an average salary of $130,371 per year, or $62.7 per hour.

High Frequency Trading Quant Researcher (Equities)

Quanta Search

New York, NY • On-site

Full-time

Posted 18 days ago

Job description

Our client, a global prop trading firm, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by their unparalleled access to a wide range of publicly available data sources.
They are growing and looking to hire an Equities Quant Analyst
Role/Responsibilities:
• Perform rigorous and innovative research to discover systematic anomalies in the equities
market
• End-to-end development, including alpha idea generation, data processing, strategy backtesting,
optimization, and production implementation
• Identify and evaluate new datasets for stock return prediction
• Maintain and improve portfolio trading in a production environment
• Contribute to the analysis framework for scalable research
Requirements:
• MS or PhD in mathematics, statistics, machine learning, computer science, engineering,
quantitative finance, or economics
• 3+ years of work experience in systematic alpha research in cash equities, with exposures to
statistical arbitrage or alternative data research
• Fluency in data science practices, e.g., feature engineering. Experience with machine learning is
a plus
• Experience with signal blending and portfolio construction
• Demonstrated proficiency in Python
• Highly motivated, willing to take ownership of his/her work
• Collaborative mindset with strong independent research abilities
• Commitment to the highest ethical standards
Thank you for illuminating hiring with Quanta Search!
www.quantasearch.com

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