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Machine Learning Quant Jobs in New Jersey (NOW HIRING)

$63.75 - $84/hr

Data Science and Machine Learning technologies ( Ex: pandas, scikit-learn, HPO ) * [Desired] Degree in a quantitative discipline (Computer Science, Applied Mathematics, Operations Research) * Top ...

$56 - $72.25/hr

Data Science and Machine Learning technologies ( Ex: pandas, scikit-learn, HPO ) * [Desired] Degree in a quantitative discipline (Computer Science, Applied Mathematics, Operations Research) * Secret ...

Lead Data Scientist

Woodcliff Lake, NJ · On-site

$181K - $201K/yr

... machine learning methods, and recommend improvements; work with large data sets from inside and ... Experience must include (quantitative experience requirements not applicable to this section)

Lead Data Scientist

Woodcliff Lake, NJ · On-site

$181.71 - $201.30/hr

... machine learning methods, and recommend improvements; work with large data sets from inside and ... Experience must include (quantitative experience requirements not applicable to this section)

Showing results 41-60

Machine Learning Quant information

See New Jersey salary details

$53.3K

$121K

$199.5K

How much do machine learning quant jobs pay per year?

As of Aug 17, 2026, the average yearly pay for machine learning quant in New Jersey is $120,981.00, according to ZipRecruiter salary data. Most workers in this role earn between $79,700.00 and $154,800.00 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 Jersey?

The most popular types of Machine Learning Quant jobs in New Jersey are:

What are popular job titles related to Machine Learning Quant jobs in New Jersey?

For Machine Learning Quant jobs in New Jersey, the most frequently searched job titles are:

Infographic showing various Machine Learning Quant job openings in New Jersey as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 21% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $120,981 per year, or $58.2 per hour.

Principal Data Scientist Predictive Formulation & Food Innovation

TalentFish LLC

Bridgewater, NJ • On-site

Other

Medical, Retirement, PTO

Posted 5 days ago


Job description

Job Title: Principal Data Scientist Predictive Formulation & Food Innovation
Location: Bridgewater, NJ (Hybrid onsite 3 days per week)
Position: Full-Time Direct Hire

Overview
TalentFish is seeking a Principal Data Scientist, Digital Innovation and Predictive Formulations to lead the technical strategy, architecture, and execution of advanced data science capabilities for a global food and ingredient innovation organization.

  • The Principal Data Scientist reports to the Director of Digital Innovation. This is a highly visible, hands-on technical leadership role for someone who can establish a long-term data science vision, build production-ready machine learning capabilities, advise business and technical leaders, and mentor other data scientists.
  • This principal-level professional will design and scale an adaptive data lakehouse and analytical framework that transforms complex scientific and formulation data into actionable insights.
  • The individual will help food scientists and product formulators use data to improve ingredient selection, guide experimentation, develop predictive formulations, and accelerate customer-focused product innovation.

Ideal Candidate Profile
This individual should be visionary, intellectually curious, collaborative, comfortable mentoring others, and equally capable of strategic thinking and hands-on technical execution. The strongest candidate will have the following 3 capabilities:

  • Principal-Level Data Science Leadership: Someone who has established technical strategy and delivered multiple high-impact data science initiatives from concept through measurable business results.
  • Data and Machine Learning Architecture: Someone capable of designing a scalable Google Cloud data lakehouse, analytical layer, and production machine learning pipelines rather than focusing only on individual models.
  • Scientific and Business Partnership: Someone who can work effectively with scientists, product-development professionals, engineers, and executives while translating complex technical concepts into clear business value.

What You'll Bring

  • A bachelor's degree or advanced degree in data science, statistics, mathematics, computer science, engineering, or another relevant quantitative field.
  • Principal-level technical leadership skills with the ability to influence strategy without relying solely on formal authority.
  • Significant professional experience in predictive modeling, data science, statistical analysis, and advanced analytics.
  • Demonstrated ability to establish a long-term technical vision and successfully execute that vision through production implementation.
  • Proven delivery of multiple major data science initiatives that generated measurable value and actionable insight for business stakeholders.
  • Experience translating ambiguous business or scientific questions into analytical approaches and practical solutions using available data.
  • Strong experience designing, building, or scaling enterprise data frameworks, analytical environments, or data lakehouse architectures.
  • Experience developing and deploying scalable machine learning models and production machine learning pipelines.
  • Strong programming and data scripting skills using Python and SQL.
  • Advanced knowledge of statistical methods, predictive modeling, machine learning, and analytical experimentation.
  • Experience with advanced modeling approaches such as Bayesian inference.
  • Strong understanding of data architecture, analytical layers, model deployment, and the operational requirements needed to move data science solutions into production.
  • Experience working within a cloud-based data and analytics environment.
  • Exceptional stakeholder management, collaboration, presentation, and communication skills.
  • Demonstrated ability to mentor technical professionals and support their continued development.
  • A results-oriented approach focused on measurable value, business outcomes, and key performance indicators.

Highly Preferred Qualifications

  • Strong hands-on experience within the Google Cloud ecosystem .
  • Experience architecting or scaling a Google Cloud data lakehouse and analytical layer.
  • Background supporting food science, food product development, ingredient solutions, formulation science, chemicals, consumer products, or another scientific research and development environment.
  • Experience applying data science to ingredient selection, formulation optimization, experimentation, or product innovation.
  • Familiarity with generative AI, modern machine learning platforms, and emerging advanced modeling techniques.
  • Experience working with global and cross-functional groups that include data scientists, engineers, business leaders, researchers, formulators, or scientific professionals.

What You'll Do

  • Lead the design and implementation of a robust, scalable data framework that can evolve with the organization's innovation and product-development needs.
  • Architect and scale a dynamic data lakehouse and democratized analytical layer within the Google Cloud ecosystem.
  • Create data capabilities that support ingredient selection, predictive formulation, scientific experimentation, and customer-focused product innovation.
  • Partner with engineering and technical teams to establish scalable machine learning pipelines that can adapt quickly to emerging business and scientific challenges.
  • Develop, validate, deploy, and continuously improve machine learning models aligned with evolving business needs.
  • Apply advanced statistical and machine learning techniques to complex, real-world business and product-development challenges.
  • Translate business and scientific questions into structured analytical problems and data-driven solutions.
  • Identify and prioritize high-value data science and AI use cases in partnership with digital innovation leadership.
  • Demonstrate the measurable business value, insight, and impact delivered by data science initiatives.
  • Establish the long-term technical vision for predictive modeling, data science, analytics, and supporting data architecture.
  • Serve as a trusted technical advisor to business leaders, scientific teams, data professionals, and other stakeholders.
  • Communicate complex technical concepts clearly to technical, business, scientific, and nontechnical audiences.
  • Mentor and develop data scientists while fostering a culture of technical excellence, curiosity, collaboration, and continuous improvement.
  • Evaluate emerging capabilities, including generative AI, machine learning platforms, and advanced modeling techniques.
  • Balance multiple opportunities while prioritizing initiatives based on measurable outcomes, business value, and key performance indicators.

Compensation and Employment
This role requires authorization to work in the U.S. without current or future visa sponsorship. The expected salary range for this position is $123,000 - $164,700 per year, depending on experience and qualifications. This role also qualifies for comprehensive benefits such as health insurance, 401(k), and paid time off. TalentFish is committed to pay transparency and equal opportunity. The salary range provided is in compliance with applicable state and federal regulations.
All offers are contingent upon the completion of a background check, which may include but is not limited to reference checks, education verification, employment verification, drug testing, criminal records checks, and any required certifications or compliance requirements based on the end client's background check policies and applicable laws.
TalentFish is an employee-owned company pioneering a new realm in talent acquisition. We are redefining IT staffing by evolving AI, video screening, and our unique platform. TalentFish focuses on providing the best employee, consultant, and client experience possible. At TalentFish we are an Equal Opportunity Employer; we embrace and encourage diversity.