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Scientific Machine Learning Jobs in Berkeley Heights, NJ

Machine Learning Engineer

New York, NY · On-site +1

$209K - $250K/yr

Job Requirements: Master's degree in Computer Science, Statistics, Data Science, or related ... Machine Learning (ML) and artificial intelligence (Al) tools Data Preprocessing, Exploration and ...

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Scientific Machine Learning information

See Berkeley Heights, NJ salary details

$14

$32

$54

How much do scientific machine learning jobs pay per hour?

As of Sep 3, 2026, the average hourly pay for scientific machine learning in Berkeley Heights, NJ is $32.85, according to ZipRecruiter salary data. Most workers in this role earn between $20.05 and $41.88 per hour, depending on experience, location, and employer.

What is scientific machine learning?

Scientific machine learning (SciML) is an interdisciplinary field that combines principles from machine learning and scientific computing to solve complex scientific and engineering problems. It involves developing algorithms and models that can learn from data and physical laws, such as differential equations, to make predictions, optimize systems, or gain insights into phenomena. SciML is widely used in areas like physics, biology, climate science, and engineering, enabling researchers to accelerate simulations and make data-driven discoveries. The field often leverages both traditional numerical methods and modern machine learning techniques, making it a rapidly evolving area of research.

What are the key skills and qualifications needed to thrive as a scientific machine learning professional, and why are they important?

To thrive as a Scientific Machine Learning professional, you need a strong background in mathematics, statistics, programming (often Python), and domain-specific scientific knowledge, typically with a graduate degree in a STEM field. Proficiency in machine learning frameworks (such as TensorFlow or PyTorch), scientific computing tools (like NumPy, SciPy), and experience with high-performance computing are commonly required. Critical thinking, problem-solving, and collaborative communication are vital soft skills for designing experiments and interpreting complex data. These skills ensure robust, reproducible results and the ability to bridge scientific inquiry with advanced computational methods.

What are some common challenges faced by professionals in scientific machine learning, and how can they be addressed?

Professionals in Scientific Machine Learning often encounter challenges such as integrating domain-specific scientific knowledge with machine learning models, managing large and complex datasets, and ensuring that models are interpretable and physically consistent. Collaboration with domain experts and interdisciplinary teams is essential to bridge knowledge gaps and validate results. To address these challenges, it is helpful to invest time in understanding the underlying scientific principles, keep up-to-date with advancements in both machine learning and scientific fields, and utilize specialized tools and frameworks designed for scientific data.

What is the difference between Scientific Machine Learning vs Data Scientist?

AspectScientific Machine LearningData Scientist
Required credentialsAdvanced degrees in CS, ML, or related fields; knowledge of scientific computingDegree in CS, statistics, or related fields; strong analytical skills
Work environmentResearch labs, academia, industry R&D teamsBusiness analytics, tech companies, consulting firms
Industry usageResearch, scientific computing, engineering simulationsBusiness insights, predictive modeling, data analysis

Scientific Machine Learning focuses on integrating scientific knowledge with machine learning techniques for research and engineering applications. Data Scientists analyze data to extract insights and build predictive models for business or operational purposes. While both roles require strong technical skills, Scientific Machine Learning emphasizes scientific computing and domain-specific modeling, whereas Data Scientists focus on data analysis and visualization.

What are popular job titles related to Scientific Machine Learning jobs in Berkeley Heights, NJ?

For Scientific Machine Learning jobs in Berkeley Heights, NJ, the most frequently searched job titles are:

What job categories do people searching Scientific Machine Learning jobs in Berkeley Heights, NJ look for?

The top searched job categories for Scientific Machine Learning jobs in Berkeley Heights, NJ are:

What cities near Berkeley Heights, NJ are hiring for Scientific Machine Learning jobs?

Cities near Berkeley Heights, NJ with the most Scientific Machine Learning job openings:

Infographic showing various Scientific Machine Learning job openings in Berkeley Heights, NJ as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 22% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $68,331 per year, or $32.9 per hour.

Machine Learning Engineer

Spgi

New York, NY • On-site, Remote

$209K - $250K/yr

Full-time

Medical, Retirement

Re-posted 6 days ago


Job description

About the Role:

Grade Level (for internal use):

11

Company Name: Kensho Technologies LLC

Job Title: Machine Learning Engineer

Location: 55 Water Street, New York, NY 10041 (Telecommuting permitted within normal commuting distance of New York, NY office)

Job Duties: Kensho Technologies LLC seeks a Machine Learning Engineer who will identify, research, prototype, and build predictive data-driven products based on statistical analysis and machine learning. Conduct original research and data analysis on large proprietary and open-source data sets to identify interesting patterns, associations, correlations, outliers, and anomalies. Formulate and test hypotheses about the distributions and regularities underlying the data. Design, implement, and evaluate statistical and machine learning models for explaining and predicting patterns in vast amounts of financial data, including financial documents. Write production code implementing predictive models and algorithms. Write tests to ensure the robustness and reliability of productionized models. Conduct peer review of research, prototypes, models, and code. Remain current in the theory and application of statistical and machine learning techniques. Maintain and acquire expertise with tools and packages for numerical and statistical programming, data analysis, and machine learning modeling.

Job Requirements: Master's degree in Computer Science, Statistics, Data Science, or related quantitative field plus one (1) year of experience in data science or a related quantitative occupation. One (1) year of experience must include: Machine Learning (ML) and artificial intelligence (Al) tools Data Preprocessing, Exploration and Visualization tools, including Jupyter, Matplotlib, Pandas, Scikit-learn; Data Management and Storage tools; Deployment and Machine Learning operations; Conducting and publishing Machine Learning research and producing code; Agentic systems, including Large Language Model (LLM) code generation and tool utilization.

The anticipated base salary range for this position is $209,000 to $250,300. Final base salary for this role will be based on the individual's geographic location, as well as experience level, skill set, training, licenses & certifications. In addition to base compensation, this role is eligible for an annual incentive plan. Kensho Technologies LLC is part of S&P Global and this role is eligible to receive additional S&P Global benefits. For more information on the benefits we provide to our employees, please see: https://spgbenefits.com/benefit-summaries/us.

THIS NOTICE IS BEING POSTED AS THE RESULT OF THE FILING OF AN APPLICATION FOR PERMANENT ALIEN LABOR CERTIFICATION. ANY PERSON MAY PROVIDE DOCUMENTARY EVIDENCE BEARING ON THE APPLICATION TO THE CERTIFYING OFFICER OF THE U.S. DEPARTMENT OF LABOR AT:

Certifying Officer

U.S. Department of Labor

Employment and Training Administration

Office of Foreign Labor Certification

200 Constitution Avenue, NW

Room N-5311

Washington, DC 20210

About S&P Global Dow Jones Indices

At S&P Dow Jones Indices, we provide iconic and innovative index solutions backed by unparalleled expertise across the asset-class spectrum. By bringing transparency to the global capital markets, we empower investors everywhere to make decisions with conviction. We're the largest global resource for index-based concepts, data and research, and home to iconic financial market indicators, such as the S&P 500 and the Dow Jones Industrial Average. More assets are invested in products based upon our indices than any other index provider in the world. With over USD 7.4 trillion in passively managed assets linked to our indices and over USD 11.3 trillion benchmarked to our indices, our solutions are widely considered indispensable in tracking market performance, evaluating portfolios and developing investment strategies.

S&P Dow Jones Indices is a division of S&P Global (NYSE: SPGI). S&P Global is the world's foremost provider of credit ratings, benchmarks, analytics and workflow solutions in the global capital, commodity and automotive markets. With every one of our offerings, we help many of the world's leading organizations navigate the economic landscape so they can plan for tomorrow, today. For more information, visit www.spglobal.com/spdji.

What's In It For You?

Our Mission:

Advancing Essential Intelligence.

Our People:

We're more than 35,000 strong worldwide-so we're able to understand nuances while having a broad perspective. Our team is driven by curiosity and a shared belief that Essential Intelligence can help build a more prosperous future for us all.From finding new ways to measure sustainability to analyzing energy transition across the supply chain to building workflow solutions that make it easy to tap into insight and apply it. We are changing the way people see things and empowering them to make an impact on the world we live in. We're committed to a more equitable future and to helping our customers find new, sustainable ways of doing business. Join us and help create the critical insights that truly make a difference.

Our Values:

Integrity, Discovery, Partnership


Throughout our history, the world's leading organizations have relied on us for the Essential Intelligence they need to make confident decisions about the road ahead. We start with a foundation of integrity in all we do, bring a spirit of discovery to our work, and collaborate in close partnership with each other and our customers to achieve shared goals.
Benefits:

We take care of you, so you cantake care of business. We care about our people. That's why we provide everything you-and your career-need to thrive at S&P Global.
Our benefits include:

  • Health & Wellness: Health care coverage designed for the mind and body.

  • Flexible Downtime: Generous time off helps keep you energized for your time on.

  • Continuous Learning: Access a wealth of resources to grow your career and learn valuable new skills.

  • Invest in Your Future: Secure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs.

  • Family Friendly Perks: It's not just about you. S&P Global has perks for your partners and little ones, too, with some best-in class benefits for families.

  • Beyond the Basics: From retail discounts to referral incentive awards-small perks can make a big difference.

For more information on benefits by country visit: https://spgbenefits.com/benefit-summaries

Global Hiring and Opportunity at S&P Global:

At S&P Global, we are committed to fostering a connected andengaged workplace where all individuals have access to opportunities based on their skills, experience, and contributions. Our hiring practices emphasize fairness, transparency, and merit, ensuring that we attract and retain top talent. By valuing different perspectives and promoting a culture of respect and collaboration, we drive innovation and power global markets.

Recruitment Fraud Alert:

If you receive an email from a spglobalind.com domain or any other regionally based domains, it is a scam and should be reported toreportfraud@spglobal.com. S&P Global never requires any candidate to pay money for job applications, interviews, offer letters, "pre-employment training" or for equipment/delivery of equipment. Stay informed and protect yourself from recruitment fraud by reviewing our guidelines, fraudulent domains, and how to report suspicious activityhere.

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Equal Opportunity Employer

S&P Global is an equal opportunity employer and all qualified candidates will receive consideration for employment without regard to race/ethnicity, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, marital status, military veteran status, unemployment status, or any other status protected by law. Only electronic job submissions will be considered for employment.

If you need an accommodation during the application process due to a disability, please send an email to:EEO.Compliance@spglobal.comand your request will be forwarded to the appropriate person.
US Candidates Only:The EEO is the Law Poster http://www.dol.gov/ofccp/regs/compliance/posters/pdf/eeopost.pdfdescribes discrimination protections under federal law. Pay Transparency Nondiscrimination Provision - https://www.dol.gov/sites/dolgov/files/ofccp/pdf/pay-transp_%20English_formattedESQA508c.pdf

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20 - Professional (EEO-2 Job Categories-United States of America), RESECH202.2 - Middle Professional Tier II (EEO Job Group), SWP Priority - Ratings - (Strategic Workforce Planning)