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Machine Learning Co Op Jobs in Chicago, IL (NOW HIRING)

Job Overview Donson Machine is a family-owned medical device manufacturer focused on providing ... With Op for further OT Night Shift (4:30PM - 3:00AM, Mon - Thurs) *With opportunity for overtime ...

Swiss/Turning Machinist

Alsip, IL · On-site

$18 - $45/hr

Job Overview Donson Machine is a family-owned medical device manufacturer focused on providing ... With Op for further OT Night Shift (4:30PM - 3:00AM, Mon - Thurs) *With opportunity for overtime ...

... Fall Co-op running from May-December. As a Project Engineer Intern, you will assist the project team in the completion of designated projects while focusing on learning construction industry ...

... Fall Co-op running from May-December. As a Project Engineer Intern, you will assist the project team in the completion of designated projects while focusing on learning construction industry ...

Maximize sales revenue, profit, and vendor co-op for specific product categories through strategic ... We value adopting AI as a partner, openness to experimentation, and a shared interest in learning ...

Showing results 41-60

Machine Learning Co Op information

See Chicago, IL salary details

$26.3K

$43.9K

$90.7K

How much do machine learning co op jobs pay per year?

As of Sep 3, 2026, the average yearly pay for machine learning co op in Chicago, IL is $43,867.00, according to ZipRecruiter salary data. Most workers in this role earn between $33,500.00 and $47,400.00 per year, depending on experience, location, and employer.

What is the difference between Machine Learning Co Op vs Data Scientist?

AspectMachine Learning Co OpData Scientist
Required CredentialsTypically pursuing a degree in CS, Data Science, or related fields; internships often preferredUsually holds a bachelor's or master's in Data Science, Statistics, or related fields; advanced certifications beneficial
Work EnvironmentInternship setting, often part-time or seasonal, in tech or research companiesFull-time role in various industries, including tech, finance, healthcare, with collaborative teams
Employer & Industry UsageUsed by companies for training and evaluating potential future employees; common in tech and research sectorsHired for analyzing data, building models, and deriving insights; prevalent across multiple industries

While both roles involve working with data and algorithms, a Machine Learning Co Op is typically an internship aimed at gaining experience, whereas a Data Scientist is a full-time professional responsible for developing and deploying data models. The Co Op provides a stepping stone into the field, often leading to a full-time Data Scientist position.

What are the most commonly searched types of Machine Learning jobs in Chicago, IL?

The most popular types of Machine Learning jobs in Chicago, IL are:

What cities near Chicago, IL are hiring for Machine Learning Co Op jobs?

Cities near Chicago, IL with the most Machine Learning Co Op job openings:

Infographic showing various Machine Learning Co Op job openings in Chicago, IL as of August 2026, with employment types broken down into 1% As Needed, 77% Full Time, 21% Part Time, and 1% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $43,867 per year, or $21.1 per hour.

SAP Product Owner

Excelon Solutions

Chicago, IL • On-site

Other

This job post has expired 3 days ago. Applications are no longer accepted.


Job description

  • Demand Planning IT systems (SAP APO DP transition to SAP IBP Demand / S/4HANA) global strategy, roadmap, release plans define.
  • Business Leadership (Supply Chain, S&OP, Commercial teams) alignment create.

Backlog & Agile Management:

  • Scrum team (Developers, Functional Consultants, Architects) product backlog groom, prioritize.
  • Clear User Stories, Business Acceptance Criteria, Functional Specifications draft.
  • Sprint Planning, Daily Stand-ups, Sprint Reviews, Demos actively lead.

Business Engagement & Requirement Gathering:

  • Global Business Stakeholders, Demand Planners, Supply Chain Leads requirements elicit, analyze, validate.
  • As-Is process gaps identify To-Be scalable SAP IBP/APO architecture design.

Technical & Domain Delivery:

  • Statistical Forecasting models, Consensus Demand Planning, Promotion Planning, Machine Learning / AI-driven forecasting capabilities optimize.
  • Master Data (CVCs, Product Hierarchies), CPI-DS/SDI Integration (S/4HANA/ECC to IBP/APO) proper flow ensure.
  • System Migration: Legacy SAP APO DP systems SAP Integrated Business Planning (IBP Demand & S&OP) migration drive.