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Scientific Machine Learning Jobs in Somerset, NJ

Working across disciplines-from architecture and ecology to materials science and computation, we ... Develop machine learning models for geospatial inference of key ecosystem metrics, leveraging ...

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 ...

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Trenton, NJ · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Showing results 21-40

Scientific Machine Learning information

See Somerset, NJ salary details

$14

$33

$55

How much do scientific machine learning jobs pay per hour?

As of Sep 3, 2026, the average hourly pay for scientific machine learning in Somerset, NJ is $33.26, according to ZipRecruiter salary data. Most workers in this role earn between $20.34 and $42.40 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 job categories do people searching Scientific Machine Learning jobs in Somerset, NJ look for?

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

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

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

$130K - $170K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 17 days ago


Key responsibilities

  • Design and maintain complex data and ML pipelines using Airflow and dbt to ensure data integrity and model reliability.

  • Transition experimental models into robust, scalable production services and build the supporting pipelines.

  • Apply advanced statistical modeling and hypothesis testing to validate models and ensure outcomes are testable and honest.


Colgate-Palmolive rating

6.4

Company rating: 6.4 out of 10

Based on 23 frontline employees who took The Breakroom Quiz


Job description

No Relocation Assistance Offered
Job Number #174332 - New York, New York, United States
Who We Are
Colgate-Palmolive Company is a global consumer products company operating in over 200 countries specializing in Oral Care, Personal Care, Home Care, Skin Care, and Pet Nutrition. Our products are trusted in more households than any other brand in the world, making us a household name!
Join Colgate-Palmolive, a caring, innovative growth company reimagining a healthier future for people, their pets, and our planet. Guided by our core values—Caring, Inclusive, and Courageous—we foster a culture that inspires our people to achieve common goals. Together, let's build a brighter, healthier future for all.
 

*This role can sit in our Park Ave (NYC) or Piscataway, NJ office*

Role Summary

We are seeking a Machine Learning Engineer who brings the analytical rigor of a data scientist and the engineering discipline of a software architect. In support of Colgate-Palmolive’s purpose to Make More Smiles and our commitment to a healthier future for our people, pets, and planet, this role builds the advanced machine learning capabilities that power smarter decisions, accelerate innovation, and create measurable impact across our global enterprise.

As part of the Enterprise AI/ML Center of Excellence, you will lead the architectural design and end-to-end execution of high-priority ML initiatives. This involves integrating statistical modeling, optimization, and autonomous workflows into Colgate-Palmolive's business processes to accelerate innovation, enhance decision intelligence, and embed AI. Beyond hands-on technical work, you ensure solutions are architecturally sound, production-ready, and compliant with enterprise governance standards, translating strategy into robust execution aligned with stakeholder needs and long-term value creation.

Responsibilities:

  • Productionize ML Research: Transition experimental models into robust, scalable production services. You don't just build the model; you build the pipeline that sustains it.

  • Pipeline Orchestration: Design and maintain complex data and ML pipelines using Airflow and dbt to ensure data integrity and model reliability.

  • Statistical Rigor: Apply advanced statistical modeling and hypothesis testing to validate models, ensuring outcomes are testable and honest.

  • DevOps & MLOps: Utilize modern developer tools to work within and CI/CD frameworks for ML and software lifecycle management

Required Qualifications: 

  • Bachelor’s Degree (or higher) in a high-rigor field: Statistics, Physics, Chemistry, Mathematics, Data Science, or Computer Science with a heavy emphasis on Statistical Learning.

  • Experience: Bachelors degree: 6+ of  years of technical experience; Masters or PhD (3+ years) 

Preferred Qualifications:

  • Proven expertise in Data Science and/or Machine Learning Engineering.

  • Advanced proficiency in Python (Production-grade) and SQL.

  • Hands-on experience with Airflow for orchestration and dbt for transformation.

  • Familiarity with modern IDEs and Agentic Coding systems (e.g., Cursor, Windsurf, Claude Code, Antigravity) to maximize output velocity.

  • Modern Stack: Expert knowledge of Python, Scikit-learn, major ML Libraries

  • Data Engineering: Deep understanding of data lifecycle (ETL/ELT), data architecture, best practices for templatized data transformation

  • Engineering Excellence: Familiar with Docker/Kubernetes, CI/CD, Git, and "Software Engineering for ML" best practices.

  • LLM Literacy: Familiar with concepts underpinning LLMs, and strategies to integrate GenAI into MLE project lifecycle


Compensation and Benefits
Salary Range $130,000.00 - $170,000.00 USD
Pay is determined based on experience, qualifications, and location. Salaried employees may also be eligible for discretionary bonuses, profit-sharing, and long-term incentives for Executive-level roles.
Benefits: Salaried employees enjoy a comprehensive benefits package, including medical, dental, vision, basic life insurance, paid parental leave, disability coverage, and participation in the 401(k) retirement plan with company matching contributions subject to eligibility requirements. Additional benefits include a minimum of 15 vacation/PTO days (hourly employees receive a minimum of 120 hours) and 13 paid holidays (vacation days are prorated based on the employee's hire date within the calendar year). Paid sick leave is adjusted based on role and location in accordance with local laws. Detailed information regarding paid sick leave entitlements will be provided to employees upon hiring and may be subject to adjustments based on changes in legislation or company policies.
Our Commitment to Inclusion
Our journey begins with our people—developing strong talent with diverse backgrounds and perspectives  to best serve our consumers around the world and fostering an inclusive environment where everyone feels a true sense of belonging. We are dedicated to ensuring that each individual can be their authentic self, is treated with respect, and is empowered by leadership to contribute meaningfully to our business.
Equal Opportunity Employer
Colgate is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity, sexual orientation, national origin, ethnicity, age, disability, marital status, veteran status (United States positions), or any other characteristic protected by law.
Reasonable accommodation during the application process is available for persons with disabilities. Please complete this request form should you require accommodation.
For additional Colgate terms and conditions, please click here.
#LI-On-site


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About Colgate-Palmolive

Sourced by ZipRecruiter

Colgate-Palmolive is a leading global consumer products company, tightly focused on Oral Care, Personal Care, Home Care and Pet Nutrition. Colgate sells its products in over 200 countries and territories around the world under such internationally recognized brand names as Colgate, Palmolive, elmex, Tom's of Maine, Sorriso, Speed Stick, Lady Speed Stick, Softsoap, Irish Spring, Protex, Sanex, Elta MD, PCA Skin, Ajax, Axion, Fabuloso, Soupline and Suavitel, as well as Hill's Science Diet and Hill's Prescription Diet.

Industry

Manufacturing

Company size

10,000+ Employees

Headquarters location

New York, NY, US

Year founded

1806

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