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Machine Learning Data Associate Jobs in Illinois

Collaborate with senior engineers and data scientists on model deployment. * Conduct experiments and run machine learning tests. * Stay updated with the latest advancements in machine learning.

Collaborate with senior engineers and data scientists on model deployment. * Conduct experiments and run machine learning tests. * Stay updated with the latest advancements in machine learning.

Collaborate with senior engineers and data scientists on model deployment. * Conduct experiments and run machine learning tests. * Stay updated with the latest advancements in machine learning.

... data environments. Essential Duties and Responsibilities: * Design and implement novel machine learning and deep learning models tailored to internal research needs * Prototype and evaluate ...

... machine learning and artificial intelligence, and other data science techniques to explore, create ... As an Inmar Associate, you: * Put clients first and consistently display a positive attitude and ...

... data environments. Essential Duties and Responsibilities: * Design and implement novel machine learning and deep learning models tailored to internal research needs * Prototype and evaluate ...

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

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

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

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

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

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Machine Learning Data Associate information

See Illinois salary details

$9

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$29

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

As of Jun 20, 2026, the average hourly pay for machine learning data associate in Illinois is $18.16, according to ZipRecruiter salary data. Most workers in this role earn between $14.90 and $19.33 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Machine Learning Data Associate, and why are they important?

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.

What is the salary of ML data associate?

The salary of a Machine Learning Data Associate typically ranges from $40,000 to $70,000 annually, depending on experience, location, and company size. Entry-level positions may start lower, while experienced professionals with specialized skills in data annotation and tools like Python or SQL can earn higher salaries.

What are Machine Learning Data Associates?

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 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.

Is ML 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. Job satisfaction depends on individual interests and career goals in technology and data fields.

How much do ML data associates make in the US?

Machine Learning Data Associates in the US typically earn between $35,000 and $60,000 annually, depending on experience, location, and employer. Entry-level positions may start lower, while those with specialized skills in data annotation, labeling, or familiarity with tools like Labelbox or CVAT can command higher salaries.

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 does a machine learning data associate do?

A machine learning data associate is responsible for collecting, cleaning, and organizing data used to train machine learning models. They ensure data quality and consistency, often using tools like SQL, Python, or data annotation platforms, to support accurate model development and deployment.
What cities in Illinois are hiring for Machine Learning Data Associate jobs? Cities in Illinois with the most Machine Learning Data Associate job openings:
Infographic showing various Machine Learning Data Associate job openings in Illinois as of June 2026, with employment types broken down into 1% Internship, 1% As Needed, 69% Full Time, 24% Part Time, 1% Temporary, and 4% Contract. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution, with an average salary of $37,767 per year, or $18.2 per hour.

Machine Learning Engineer

Kasmo Global

Chicago, IL

Other

Posted 5 days ago


Job description

Machine Learning Engineer

Location: San Jose, CA/Chicago, IL

Duration: 18 months contract with a possible extension

What You'll Do

• Redesign and optimize PayPal's MLOps and decision platform for fraud detection

• Architect large-scale big-data infrastructure to enable use of cutting-edge machine learning models for real-time fraud prevention.

• Collaborate with data scientists and platform engineers to automate workflow

• Provide solutions that ensure compliance, security, and maintainability across the fraud detection ecosystem.

• Work with high-dimensional datasets and leverage tools like Python, PySpark, and Big Query to develop robust workflows for fraud signal detection.

• Standardize rules and decision processes while enabling dynamic rule updates and analytics within the fraud detection platform.

• Collaborate across multidisciplinary teams in engineering, product development, and data science to scale solutions globally.

• Tasks will be distributed via our Jira board/sprint planning/grooming cycle.

• Team will have a regular standup on each task (at least twice a week but open for daily if needed or any blockers).

• During the onboarding, it would require more interactions with Engg/Product/US Risk core teams but once onboarded, it would be 50/50.

• Team work mostly within Jira board from tasks assignments and tracking.

• Code would be in our centralized GitHub repo.

• Updates/documentation would be either in wiki page or our SharePoint/share drive.

You would get chance to design and implement scalable solutions to optimize fraud detection systems, spanning model development, feature engineering, and rule-based systems. You will collaborate closely with cross-functional teams, including data scientists, engineers, and product managers, to ensure our platform sets a new global standard for efficacy and innovation. You will address critical business challenges, develop advanced automation frameworks, and integrate cutting-edge machine learning techniques to enhance decision-making capabilities. By joining us, you will not only contribute to PayPal's fraud detection efforts but leave a lasting impact on the financial security of millions of users around the globe.

Top Skills:
  • Big Query, Python, SQL
  • Understand the production systems architect and offline data overview
  • Machine Learning experience