ZipRecruiter

Log In

1

Machine Learning Quant Jobs in New York (NOW HIRING)

Umbrex

Hedge Fund Quant Analyst - Umbrex

Manhattan, NY · On-site

$100 - $125/hr

Our client is building an equity trading engine powered by machine learning. They are seeking a Hedge Fund Quant Analyst with deep expertise in equity trading, advanced modeling techniques, and ...

Capital Rx

Senior Machine Learning Engineer

Manhattan, NY · On-site

$161K - $202K/yr

Bachelor's or Master's degree in Computer Science, Machine Learning, or a related quantitative field. * Minimum 4+ years of experience in industry with a strong focus on ML solutions development and ...

Injective Labs

Quant Researcher

New York, NY · On-site +1

  • Medical

  • PTO

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 ...

Bloomberg LP

Product Manager - Enterprise Data

New York, NY · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

You'll bring with you a few years working in a financial or technology firm in the machine learning/quantitative trading domain, along with some programming and data management skills. You'll work ...

previous page

Showing results 41-60

All JobsMachine Learning Quant JobsMachine Learning Quant Jobs in New York

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 Aug 18, 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?

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 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 key skills and qualifications needed to thrive as a machine learning quant?

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 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 August 2026, with employment types broken down into 100% Full Time. Highlights an 79% In-person, 10% Hybrid, and 11% Remote job distribution, with an average salary of $130,371 per year, or $62.7 per hour.

Manager, Data Science - Consumer Identity Machine Learning

Capital One

New York, NY • On-site

Full-time

Re-posted 8 hours ago

Capital One rating

7.7

Company rating: 7.7 out of 10

Based on 147 frontline employees who took The Breakroom Quiz

92nd of 171 rated banks

Job description

Manager, Data Science - Consumer Identity Machine Learning

Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making.

As a Data Scientist at Capital One, you'll be part of a team that's leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.

Team Description:

Consumer Identity ML is the data science and machine learning team inside Capital One's AI foundation organization. We deliver real-time, personalized, intelligent customer experiences in Capital One's suite of award-winning digital products, including our website, mobile app, emails, chatbot, and beyond. We partner closely with our product and engineering teams to build the data and modeling platforms crucial to the deep understanding of customers that enables our applications to delight them by adapting to their needs.

As part of Consumer ML, you will:

  • Explore billions of clickstream events to discover the patterns in customer behavior, and use those patterns to model key customer outcomes

  • Develop the real-time models that use vast amounts of customer data to anticipate customers' needs and deliver the right options at the right time

  • Develop the models that ensure our most important customer data is accurate, fighting fraud and other bad behavior, while enabling seamless digital experiences across all our products

Role Description:

In Consumer Identity ML, you will work at all phases of the data science life cycle, including:

  • Build machine learning models through all phases of development, from design through training, evaluation and validation, and partner with engineering teams toimprove operationalizationin scalable and resilient production systems that serve 50+ million customers.

  • Partner closely with a variety of business and product teams across Capital One to conduct the experiments that guide improvements to customer experiences and business outcomes in domains like marketing, servicing and fraud prevention.

  • Write software (Python, e.g.) to collect, explore, visualize and analyze numerical and textual data (billions of customer transactions, clicks, payments, etc.) using tools like Spark.

The Ideal Candidate is

  • Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them.

  • Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You're not afraid to share a new idea.

  • Technical. You're comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing data science solutions using open-source tools and cloud computing platforms.

  • Statistically-minded.You've built models, validated them, and back tested them. You know how to interpret a confusion matrix or a ROC curve. You have experience with clustering, classification, sentiment analysis, time series, and deep learning.

  • A data guru. "Big data" doesn't faze you. You have the skills to retrieve, combine, and analyze data from a variety of sources and structures. You know understanding the data is often the key to great data science.


Basic Qualifications:

  • Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date:

    • A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 6 years of experience performing data analytics

    • A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 4 years of experience performing data analytics

    • A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 1 year of experience performing data analytics

  • At least 1 year of experience leveraging open source programming languages for large scale data analysis

  • At least 1 year of experience working with machine learning

  • At least 1 year of experience utilizing relational databases


Preferred Qualifications:

  • PhD in "STEM" field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics

  • At least 1 year of experience working with AWS

  • At least 4 years' experience in Python, Scala, or R for large scale data analysis

  • At least 4 years' experience with machine learning

  • At least 4 years' experience with SQL


Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

McLean, VA: $197,300 - $225,100 for Mgr, Data Science


New York, NY: $215,200 - $245,600 for Mgr, Data Science


San Francisco, CA: $215,200 - $245,600 for Mgr, Data Science


San Jose, CA: $215,200 - $245,600 for Mgr, Data Science








Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter.

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.

Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at theCapital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.

If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

What Capital One employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Apply