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Temporary Machine Learning Quant Jobs (NOW HIRING)

Quanta Search

Machine Learning Engineer

Manhattan, NY · On-site

This division offers an array of quantitative investment fund products to its clients. They are ... Machine Learning Engineers build production grade machine learning algorithms that operate in real ...

Quanta Search

Machine Learning Engineer

Manhattan, NY · On-site

Thisdivision offers an array of quantitative investment fund products to its clients. They are ... Machine Learning Engineers build production grade machine learning algorithms that operate in real ...

Initio Capital

Quantitative Analyst (Quant)

New York, NY · Remote

$145K - $185K/yr

Job Summary Quantitative Analyst (Quant) Initio Capital Full-time, Part-time, Contract, Temporary ... Statistical Analysis & Machine Learning: Use advanced statistical methods and machine learning ...

PayPal

Machine Learning Engineer

Austin, TX

This job will validate and develop machine learning models and algorithms to solve complex problems ... Conduct quantitative and qualitative model validation according to Model Risk Management Policy to ...

PayPal

Machine Learning Engineer

Chicago, IL

This job will validate and develop machine learning models and algorithms to solve complex problems ... Conduct quantitative and qualitative model validation according to Model Risk Management Policy to ...

PayPal, Inc.

Machine Learning Engineer

Chicago, IL · On-site

This job will validate and develop machine learning models and algorithms to solve complex problems ... Conduct quantitative and qualitative model validation according to Model Risk Management Policy to ...

Judi Health

Machine Learning Engineer

Denver, CO · Remote

Bachelor's or Master's degree in Computer Science, Machine Learning, or a related quantitative field. * 2+ years experience in the industry with a strong focus on ML solutions development and ...

Judi Health

Machine Learning Engineer

New York, NY · Remote

Bachelor's or Master's degree in Computer Science, Machine Learning, or a related quantitative field. * 2+ years experience in the industry with a strong focus on ML solutions development and ...

Vizient, Inc.

AVP, Machine Learning & Modeling

Chicago, IL · On-site

$156.50K - $290.10K/yr

... and quantitative analysts. Foster a culture of innovation, continuous learning, and collaboration ... Research and Innovation Stay at the forefront of emerging AI and machine learning technologies.

IMC

Machine Learning Researcher

Chicago, IL

IMC Trading is seeking quantitative researchers with a proven track record to apply state-of-the-art machine learning & deep learning to solve challenging trading problems. This role is part of a ...

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Temporary Machine Learning Quant information

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$52.5K

$119.2K

$196.5K

How much do temporary machine learning quant jobs pay per year?

As of May 31, 2026, the average yearly pay for temporary machine learning quant in the United States is $119,165.00, according to ZipRecruiter salary data. Most workers in this role earn between $78,500.00 and $152,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Temporary Machine Learning Quant, and why are they important?

To excel as a Temporary Machine Learning Quant, you need strong quantitative analysis skills, proficiency in machine learning algorithms, and an advanced degree in a quantitative field such as mathematics, statistics, computer science, or engineering. Hands-on experience with programming languages like Python or R, familiarity with data analysis libraries (e.g., NumPy, pandas), and exposure to financial systems or platforms are typically required. Exceptional problem-solving abilities, adaptability, and effective communication help you stand out in this fast-paced environment. These competencies are crucial for developing and deploying data-driven models that inform trading strategies and deliver measurable business impact.

What are the typical responsibilities and challenges faced by a Temporary Machine Learning Quant in a financial firm?

As a Temporary Machine Learning Quant, you will often be tasked with quickly analyzing large financial datasets to develop and validate predictive models for trading strategies or risk assessment. Adapting to new team environments and rapidly understanding proprietary data systems can be challenging, especially given the short-term nature of the role. You'll collaborate closely with traders, data engineers, and other quants to implement solutions, and are usually expected to deliver actionable insights within tight deadlines. The fast-paced setting provides exposure to cutting-edge technologies and can be a stepping stone to more permanent quant or data science positions.

What does a Temporary Machine Learning Quant do?

A Temporary Machine Learning Quant is a professional who applies machine learning techniques to financial data and quantitative models, typically on a short-term or project-based contract. Their work may involve researching, developing, and implementing algorithms to analyze market trends, forecast prices, or optimize trading strategies. These roles are often found in investment banks, hedge funds, or fintech companies, and require strong programming, statistical, and financial skills. The 'temporary' aspect indicates the position is not permanent and usually fills a specific project or resource gap.

What is the difference between Temporary Machine Learning Quant vs Quantitative Analyst?

AspectTemporary Machine Learning QuantQuantitative Analyst
CredentialsDegree in Computer Science, Data Science, or related fields; programming skills in Python, R, or C++Degree in Finance, Economics, or Mathematics; strong analytical skills
Work EnvironmentTech-driven, research-focused, often in financial firms or hedge fundsFinancial institutions, investment banks, asset management firms
Industry UsageCommon in quantitative trading, algorithm development, and data-driven finance rolesUsed for risk management, trading strategies, and financial modeling

The Temporary Machine Learning Quant and Quantitative Analyst roles share overlapping skills in data analysis and finance but differ mainly in focus. The Machine Learning Quant emphasizes programming, algorithm development, and machine learning techniques, often in tech-heavy environments. In contrast, the Quantitative Analyst leans more toward financial modeling, market analysis, and risk assessment. Both roles are vital in finance but cater to different technical and strategic needs.

More about Temporary Machine Learning Quant jobs
What cities are hiring for Temporary Machine Learning Quant jobs? Cities with the most Temporary Machine Learning Quant job openings:
What are the most commonly searched types of Machine Learning Quant jobs? The most popular types of Machine Learning Quant jobs are:
What states have the most Temporary Machine Learning Quant jobs? States with the most job openings for Temporary Machine Learning Quant jobs include:
What job categories do people searching Temporary Machine Learning Quant jobs look for? The top searched job categories for Temporary Machine Learning Quant jobs are:
Temporary Machine Learning Quant jobs near you
Infographic showing various Temporary Machine Learning Quant job openings in the United States as of May 2026, with employment types broken down into 3% As Needed, 1% Full Time, 94% Part Time, and 2% Contract. Highlights an 99% Physical, and 1% Remote job distribution, with an average salary of $119,165 per year, or $57.3 per hour.

Machine Learning Engineer

Quanta Search

Manhattan, NY • On-site

Full-time

Posted 9 days ago

Job description

Our client is a process driven investment management group consisting of a team of researchers, traders and technologists who harness and apply the power of technology and automation to identify, model and trade global financial markets. This division offers an array of quantitative investment fund products to its clients.
They are seeking candidates with exceptional academic credentials to join their team and participate in and support of the firm's efforts in the research, trading and production processes.
They look for candidates who are eager to make an impact by doing real, hands-on research and development. Candidates must possess exceptional knowledge of mathematical and statistical methods as well as a proven ability to solve complex problems. A desire to work with large data sets and apply creative thinking is required. Successful candidates will also have deep interest in learning about trading and the financial markets.
They offer a supportive environment that fosters independent thought in a collegial, results oriented, work setting. Researchers and developers there are passionate about their work, model building, data and technology.
You are curious and intellectually driven to succeed. You'll be provided with the tools, resources and training required to satisfy that curiosity and passion, leading them to new insights and discoveries. Their process driven approach enables these insights to be thoroughly tested in a systematic fashion and ultimately, if confirmed, integrated into the portfolio.
Role:
Machine Learning Engineers build production grade machine learning algorithms that operate in real time or at scale. They have a very deep understanding of machine learning algorithms and cloud computing. Machine Learning Engineers should be comfortable with data engineering and should have an interest in the data science.
What they will do:
They will be responsible for their production grade signal generation and ML systems. They can act as data scientists, but should be comfortable pushing their algorithms, models, and signals into production.
Minimum Requirements:
  • Strong understanding of statistical analysis and computational modelling.
  • Strong understanding of algorithms and data structures.
  • Familiar with map reduce and big data processing (Spark, Hadoop, DataFlow, etc).
  • TensorFlow (or another GPU integrated deep learning library).
  • Deep understanding of machine learning algorithms.
  • Deep understanding of numerical optimization.
  • Strong understanding of data structures and algorithms.

Plus, but not required:
  • Previous experience in tech industry (GOOG, AMZN, FB, NFLX, Spotify, etc).
  • Experience building industrial grade ETL pipelines.
  • Experience building frontend systems.
  • Familiarity with dashboards and other visualization tools.
  • Ability to derive generalization bounds for common ML algorithms.
  • Experience developing new machine learning algorithms.

Thank you for illuminating hiring with Quanta Search!
www.quantasearch.com

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