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Machine Learning Data Associate Jobs in Philadelphia, PA

Machine Learning and Artificial Intelligence play a critical role in transforming Consumer and Community Banking Operations. The ability to utilize data in meaningful ways allows us to develop ...

New

Senior Machine Learning Engineer

Malvern, PA · On-site

$120K - $158K/yr

As part of a significant investment in Data & AI, our client is expanding its engineering organization with two newly created Machine Learning positions. This role is focused on building the ...

Machine Learning Tutor

Chester, PA · Remote

$18 - $40/hr

Guides students through data preprocessing, feature selection, building and comparing ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Trenton, NJ · Remote

$18 - $40/hr

Guides students through data preprocessing, feature selection, building and comparing ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Senior Engineer - Machine Learning

Ambler, PA · Hybrid

$100K - $138K/yr

You will work closely with product, engineering, architecture, and data teams to design, implement, and scale AI systems - ranging from predictive modeling and traditional machine learning pipelines ...

Senior Engineer - Machine Learning

Ambler, PA · On-site

$100K - $138K/yr

You will work closely with product, engineering, architecture, and data teams to design, implement, and scale AI systems - ranging from predictive modeling and traditional machine learning pipelines ...

Senior Machine Learning Engineer

Malvern, PA · On-site

$102K - $140K/yr

Develop and maintain feature engineering, feature storage, and data preparation pipelines ... Experience in software engineering, machine learning engineering, data engineering, or a related ...

Showing results 21-40

Machine Learning Data Associate information

See Philadelphia, PA salary details

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$31

How much do machine learning data associate jobs pay per hour?

As of Aug 20, 2026, the average hourly pay for machine learning data associate in Philadelphia, PA is $18.91, according to ZipRecruiter salary data. Most workers in this role earn between $15.53 and $20.14 per hour, depending on experience, location, and employer.

What is a machine learning data associate?

Machine Learning Data Associates are professionals who support the development of machine learning models by preparing, labeling, and validating data sets. Their work ensures that data used for training algorithms is accurate, consistent, and properly annotated. They may also assist with data cleaning, quality checks, and sometimes basic data analysis tasks. This role is crucial in industries where high-quality labeled data is essential for building effective AI systems.

What are the key skills and qualifications needed to thrive as a machine learning data associate?

To thrive as a Machine Learning Data Associate, you need strong analytical skills, attention to detail, and a basic understanding of data annotation and labeling processes, often supported by a degree in computer science or a related field. Familiarity with data management tools, annotation platforms, and sometimes scripting languages like Python is typically required. Strong communication, collaboration, and problem-solving abilities help you work efficiently with data science teams and ensure high-quality outcomes. These skills and qualities are crucial for producing accurate datasets that directly impact the effectiveness of machine learning models.

How does a machine learning data associate typically collaborate with data scientists and engineers within a project team?

As a Machine Learning Data Associate, you play a vital role in supporting data scientists and engineers by annotating, cleaning, and organizing large datasets to ensure high data quality. You'll frequently communicate with team members to clarify labeling guidelines, provide feedback on data inconsistencies, and report any edge cases encountered during annotation. This collaboration ensures that the datasets used for training machine learning models are accurate and comprehensive, directly impacting the success of the project. Expect regular team meetings and ongoing feedback loops to maintain alignment with evolving project requirements.

What is the difference between Machine Learning Data Associate vs Data Analyst?

AspectMachine Learning Data AssociateData Analyst
Required SkillsData cleaning, labeling, basic programming, understanding of ML workflowsData interpretation, visualization, statistical analysis
Work EnvironmentTech companies, AI startups, research labsBusiness, finance, marketing, healthcare sectors
Common CertificationsData Science certifications, Python, SQLExcel, Tableau, SQL certifications

The main difference is that Machine Learning Data Associates focus on preparing and labeling data specifically for machine learning models, while Data Analysts interpret data to generate insights for business decisions. Both roles require strong data skills and often overlap, but their primary objectives and work environments differ.

How do I become a machine learning data associate?

To become a machine learning data associate, candidates typically need a high school diploma or equivalent, with some roles preferring a bachelor's degree in computer science, data science, or related fields. Relevant skills include data annotation, understanding of machine learning concepts, and proficiency with tools like Excel, SQL, or data labeling platforms. Gaining experience through internships or certifications can improve job prospects in this field.

Is a Machine Learning Data Associate a good job?

A Machine Learning Data Associate role involves preparing and managing data for machine learning models, often requiring skills in data cleaning, annotation, and familiarity with tools like Python or SQL. It can be a good entry-level position for those interested in AI and data science, offering opportunities to develop technical skills and gain industry experience. Compensation and job satisfaction vary depending on the employer and location, but it generally provides a solid foundation for a career in machine learning or data analysis.

What cities near Philadelphia, PA are hiring for Machine Learning Data Associate jobs?

Cities near Philadelphia, PA with the most Machine Learning Data Associate job openings:

Infographic showing various Machine Learning Data Associate job openings in Philadelphia, PA as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $39,328 per year, or $18.9 per hour.

Acceleration Center- Agentic AI and Machine Learning Developer- Experienced Associate

Pwc

Philadelphia, PA

$61K - $100K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 22 days ago


PwC rating

8.3

Company rating: 8.3 out of 10

Based on 76 frontline employees who took The Breakroom Quiz

26th of 72 rated business consultants


Job description

Industry/Sector

Not Applicable

Specialism

Risk Architecture

Management Level

Associate

Job Description & Summary

The Opportunity
As an Acceleration Center- Agentic AI and Machine Learning Developer- Experienced Associate, you will be at the forefront of transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Within our Risk & Regulatory practice, you will leverage advanced technologies and techniques to design and develop robust data solutions for clients, applying data, algorithms, and software engineering to build and deploy AI and Machine Learning solutions at scale.
As an Associate, you will focus on learning and contributing to client engagements and projects, developing your skills and knowledge to deliver quality work. You will be exposed to clients to learn how to build meaningful connections, manage and inspire others, and grow your personal brand by deepening your technical knowledge of firm services and technology resources. In this role at PwC, you will design AI systems, engage in data wrangling, and implement software to enable scalable AI models, all while adapting to a fast-paced environment and diverse client needs. Embrace the opportunity to learn and grow, taking ownership of your development and consistently delivering work that drives value for our clients and success as a team.
Responsibilities
- Designing and implementing AI and machine learning solutions to transform raw data into actionable insights
- Developing scalable data models and pipelines to support AI systems and enhance data integration
- Utilizing programming languages such as Python and machine learning libraries like TensorFlow and Scikit-Learn to build and deploy AI models
- Engaging in complex data analysis to identify patterns and inform decision-making processes
- Collaborating with team members to address client challenges and deliver quality solutions
- Applying natural language processing techniques to improve text analytics and sentiment analysis
- Building and maintaining data infrastructure to support AI and machine learning initiatives
- Participating in the development of open-source software solutions to advance AI capabilities
- Conducting data wrangling and preprocessing to prepare datasets for machine learning applications
- Contributing to the continuous improvement of AI systems through feedback and iterative development
What You Must Have
- At least a Bachelor's degree
- At least 1 years of experience
What Sets You Apart
- Preference for at least one of the following fields of study: Analytics/Data Science, Artificial Intelligence/Robotics, Computer Science/Information Systems, Engineering
- At least one of the following: Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS, Google Cloud, Microsoft Azure, Databricks, Snowflake, or related data and AI credentials
- Demonstrating proficiency in Python and Scikit-Learn for machine learning tasks
- Utilizing TensorFlow and Neural Networks for advanced AI implementations
- Applying Natural Language Processing (NLP) techniques for text analytics
- Developing data pipelines and integration strategies for complex data environments
- Excelling in active listening and communication to enhance team collaboration

Travel Requirements

Up to 60%

Job Posting End Date

The salary range for this position is: $61,000 - $100,000. 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-glanceAs 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-workFor 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, the 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.

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