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Entry Level Machine Learning Jobs in River Edge, NJ

Pwc

AI & GenAI Data Scientist - Manager

New York, NY

$99K - $232K/yr

Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

Sogeti

Entry Level Technology Consultant

New York, NY · On-site

As an Entry-Level Technology Consultant at Sogeti , you wi ll join one of our core practices based ... Explore emerging tech-from artificial intelligence / machine learning to cloud-native engineering ...

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Entry Level Machine Learning information

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How much do entry level machine learning jobs pay per hour?

As of Sep 15, 2026, the average hourly pay for entry level machine learning in River Edge, NJ is $17.82, according to ZipRecruiter salary data. Most workers in this role earn between $15.96 and $19.38 per hour, depending on experience, location, and employer.

What are entry level machine learning jobs?

Entry-level machine learning jobs focus on creating and using software for the development of artificial intelligence (AI). In this role, you may help program computer software, engineer mechanical solutions, help develop learning objectives, and use analytics to determine whether or not the technology created is meeting development goals. Many entry-level machine learning jobs focus on particular parts of the industry. For example, some companies focus on surveillance and intelligence, while others are creating technology for self-driving vehicles. Employers often use this position as a type of extended learning period to help you develop your skills before you start taking responsibility for major projects.

What types of projects can an entry level machine learning professional expect to work on in their first year?

As an entry-level machine learning professional, you’ll typically start by supporting more senior data scientists and engineers with tasks such as data cleaning, exploratory data analysis, and building baseline models. You may work on pilot projects like developing recommendation systems, automating simple classification tasks, or contributing to model evaluation and performance tuning. Collaboration with cross-functional teams—including software engineers, product managers, and domain experts—is common, providing valuable exposure to real-world business problems and laying a foundation for more complex responsibilities as you gain experience.

What are the key skills and qualifications needed to thrive as an entry level machine learning engineer, and why are they important?

To thrive as an Entry Level Machine Learning Engineer, you need a solid background in mathematics, statistics, and programming (especially in Python), typically supported by a degree in computer science or a related field. Familiarity with machine learning frameworks like TensorFlow or PyTorch, version control systems like Git, and data analysis libraries is commonly required. Strong problem-solving abilities, curiosity, and effective communication skills help differentiate candidates in collaborative and fast-evolving environments. These skills and qualifications are essential for building, testing, and improving machine learning models that drive innovation and business value.

What is the difference between Entry Level Machine Learning vs Data Analyst?

AspectEntry Level Machine LearningData Analyst
Required CredentialsBachelor's in CS, Math, or related; some knowledge of programming and statisticsBachelor's in Statistics, Math, or related; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentTech companies, startups, research labs; focus on developing models and algorithmsBusiness, finance, marketing; focus on interpreting data and generating reports
Employer & Industry UsageTech, e-commerce, healthcare; roles involve building predictive modelsRetail, finance, consulting; roles involve analyzing data trends and insights

Entry Level Machine Learning roles focus on developing algorithms and models using programming and statistical skills, often in tech-driven environments. Data Analysts interpret and visualize data to support business decisions, typically using tools like Excel and SQL. While both roles require analytical skills, Machine Learning positions emphasize coding and model development, whereas Data Analysts focus on data interpretation and reporting.

How to get into entry level machine learning with no experience?

Entry level machine learning roles typically require foundational knowledge in programming, statistics, and data analysis. Gaining skills through online courses, practicing with projects, and learning tools like Python, TensorFlow, or scikit-learn can help build a portfolio. Internships, certifications, and participating in competitions like Kaggle can also improve your chances of entering the field without prior experience.
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Entry Level Machine Learning jobs near you
Infographic showing various Entry Level Machine Learning job openings in River Edge, NJ as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 23% Part Time, and 1% Contract. Highlights an 83% Physical, 3% Hybrid, and 14% Remote job distribution, with an average salary of $37,060 per year, or $17.8 per hour.

AML and Sanctions- Data Scientist- Senior Associate

Manhattan, NY • On-site

PwC South Africa
See more jobs at PwC South Africaexternal

$77K - $202K/yr

Other

Medical, Dental, Vision, Retirement, PTO

This job post has expired today. Applications are no longer accepted.

Key responsibilities

  • Apply machine learning and natural language processing techniques to financial crime challenges using data analysis tools like SQL and Python.

  • Analyze complex datasets to develop insights and solutions related to financial crime detection and machine learning models.

  • Mentor junior team members and maintain high standards while building client relationships.

Job description

Industry/Sector Banking and Capital Markets Specialism Data, Analytics & AI Management Level Senior Associate Job Description & Summary At PwC, our people in data and analytics focus on leveraging data to drive insights and make informed business decisions. They utilise advanced analytics techniques to help clients optimise their operations and achieve their strategic goals. In business intelligence at PwC, you will focus on leveraging data and analytics to provide strategic insights and drive informed decision‑making for clients. You will develop and implement innovative solutions to optimise business performance and enhance competitive advantage. Focused on relationships, you are building meaningful client connections, and learning how to manage and inspire others. Navigating increasingly complex situations, you are growing your personal brand, deepening technical expertise and awareness of your strengths. You are expected to anticipate the needs of your teams and clients, and to deliver quality. Embracing increased ambiguity, you are comfortable when the path forward isn’t clear, you ask questions, and you use these moments as opportunities to grow.

Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to: Respond effectively to the diverse perspectives, needs, and feelings of others. Use a broad range of tools, methodologies and techniques to generate new ideas and solve problems. Use critical thinking to break down complex concepts. Understand the broader objectives of your project or role and how your work fits into the overall strategy. Develop a deeper understanding of the business context and how it is changing. Use reflection to develop self awareness, enhance strengths and address development areas. Interpret data to inform insights and recommendations. Uphold and reinforce professional and technical standards (e.g. refer to specific PwC tax and audit guidance), the Firm's code of conduct, and independence requirements.

The Opportunity

As part of the Financial Crime Unit team you will apply analytical methods to complex datasets leveraging SQL and Python. As a Senior Associate you will analyze intricate problems, mentor Associates, and maintain exemplary standards while building meaningful client relationships. This role offers the chance to deepen your technical knowledge and personal brand while navigating the complexities of financial crime detection and machine learning applications.

Responsibilities
  • Apply machine learning and natural language processing to financial crime challenges
  • Develop a thorough understanding of the business landscape
  • Navigate intricate scenarios to enhance personal and technical growth
  • Leverage SQL and Python for data analysis and problem‑solving
What You Must Have
  • Bachelor's Degree in Computer and Information Science, Economics, Engineering, Operations Management/Research, Statistics, Data Processing/Analytics/Science, Mathematics
  • 3 years of professional experience in data science/machine learning
What Sets You Apart
  • Experience mentoring junior team members
  • Proven ability in developing machine learning models
  • Demonstrating advanced skills in Python and SQL
  • Familiarity with MLOps practices for model monitoring
  • Comfort working with structured and unstructured data
  • Experience with cloud platforms and containerization
  • Knowledge of agentic AI frameworks for workflows
  • Ability to translate client requirements into analytical solutions
  • Proficiency in SQL and Python
  • Hands‑on experience with ML frameworks (scikit‑learn, XGBoost, LightGBM, Hugging Face)
  • Thorough understanding of model evaluation metrics across tasks
Travel Requirements Up to 60%

The salary range for this position is: $77,000 - $202,000. Actual compensation within the range will be dependent upon the individual's skills, experience, qualifications and location, and applicable employment laws. All hired individuals are eligible for an annual discretionary bonus.

PwC offers a wide range of benefits, including medical, dental, vision, 401k, holiday pay, vacation, personal and family sick leave, and more. To view our benefits at a glance, please visit the following link: https://pwc.to/benefits-at-a-glance

As PwC is anequal opportunity employer, all qualified applicants will receive consideration for employment at PwC without regard to race; color; religion; national origin; sex (including pregnancy, sexual orientation, and gender identity); age; disability; genetic information (including family medical history); veteran, marital, or citizenship status; or, any other status protected by law.

PwC does not intend to hire experienced or entry level job seekers who will need, now or in the future, PwC sponsorship through the H-1B lottery, except as set forth within the following policy: https://pwc.to/H-1B-Lottery-Policy.

Learn more about how we work: https://pwc.to/how-we-work.

For only those qualified applicants that are impacted by the Los Angeles County Fair Chance Ordinance for Employers, the Los Angeles' Fair Chance Initiative for Hiring Ordinance, San Francisco Fair Chance Ordinance, San Diego County Fair Chance Ordinance, and the California Fair Chance Act, where applicable, arrest or conviction records will be considered for Employment in accordance with these laws. At PwC, we recognize that conviction records may have a direct, adverse, and negative relationship to responsibilities such as accessing sensitive company or customer information, handling proprietary assets, or collaborating closely with team members. We evaluate these factors thoughtfully to establish a secure and trusted workplace for all.

To view other PwC job opportunities, visit pwc.com/careers.

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