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Data Science Co Op Jobs (NOW HIRING)

True Manufacturing

AI Analyst Co-op

O Fallon, MO

Collaborate with software engineers and data scientists on AI-driven features. * Document findings ... The AI Analyst Co-op is an office-based role. Regular, predictable on-site attendance is required.

Sappi

Process Engineer Co-op

Cloquet, MN · On-site

... Science, BBE, Chemical and/or Environmental Engineering students to fill co-op positions in the ... These tasks range from field sampling and analytical testing, to data analysis, report writing ...

Dana Incorporated

IT Co-Op

Novi, MI · On-site

$14 - $18.75/hr

The IT Co Op will collaborate with IT teams and business stakeholders to support operational ... Information Technology, Information Systems, Computer Science, Software Engineering, Data Science ...

Lila Sciences

Co-Op, Data Extraction

Cambridge, MA · On-site

Within Physical Sciences AI, our team works on turning unstructured scientific knowledge (e.g ... As a Data Extraction Co-Op, you will work alongside research scientists and engineers on a focused ...

Lila Sciences

Co-op, Protein Sciences

Cambridge, MA

Your Impact at LILA Lila Sciences is seeking a dedicated Cell Free Co-op for Protein Sciences to ... Generate quality control data via plate-based assays * Prepare media and solutions for cell culture ...

ArcelorMittal

Data Analytics Co-Op

Detroit, MI · On-site

Data Analytics Co-Op Location: Detroit, MI Who Are We? Are you ready to be part of a dynamic and rapidly growing company that's shaping the future? Welcome to ArcelorMittal Tailored Blanks (AMTB ...

ArcelorMittal

Data Analytics Co-Op

Detroit, MI

Data Analytics Co-Op Location: Detroit, MI Who Are We? Are you ready to be part of a dynamic and rapidly growing company that's shaping the future? Welcome to ArcelorMittal Tailored Blanks (AMTB ...

Bridgestone Americas, Inc.

Fall 2026 Co-Op

Akron, OH · On-site

$16.75 - $21.75/hr

... and science Co-Ops. Co-Op students at Bridgestone are an integral part of the staff and are ... data analysis/processing, testing processes, equipment, raw materials and product, and validating ...

Dana Incorporated

IT Co-Op

Novi, MI · On-site

$14.25 - $18.75/hr

The IT Co Op will collaborate with IT teams and business stakeholders to support operational ... Information Technology, Information Systems, Computer Science, Software Engineering, Data Science ...

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Data Science Co Op information

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$37.5K

$122.7K

$196.5K

How much do data science co op jobs pay per year?

As of Jun 29, 2026, the average yearly pay for data science co op in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What is the 80 20 rule in data science?

The 80/20 rule in data science suggests that roughly 80% of the results come from 20% of the efforts or data. Data scientists often use this principle to focus on the most impactful features, data subsets, or models to improve efficiency and outcomes in their analyses.

Is 40 too late for data science?

Data science co-ops and entry-level roles often value skills and relevant experience over age, so starting a career at 40 is not too late. Many professionals successfully transition into data science later in life by learning programming languages like Python or R, gaining certifications, and building portfolios. Age should not be a barrier if you develop the necessary technical skills and stay current with industry tools and trends.

Which is better, DS or CS?

Data Science Co-ops focus on analyzing data, building models, and applying statistical tools, often requiring skills in programming, statistics, and data visualization. Computer Science roles emphasize software development, algorithms, and system design, typically involving programming languages like Java or C++. Both fields offer valuable career paths, but the choice depends on your interests in data analysis versus software engineering.

What kinds of projects or tasks can I expect to work on as a Data Science Co Op?

As a Data Science Co Op, you may be involved in a variety of projects such as data cleaning, exploratory data analysis, building predictive models, or generating data visualizations to support business decisions. You’ll often work alongside more experienced data scientists, analysts, and cross-functional teams to collaboratively solve real-world problems using data. This role typically emphasizes hands-on learning and practical application of analytical techniques, offering a great opportunity to develop your technical and communication skills. In addition, you may participate in regular meetings, present findings, and contribute to ongoing research or product development initiatives.

What are the key skills and qualifications needed to thrive in the Data Science Co Op position, and why are they important?

To succeed as a Data Science Co Op, you should have a solid understanding of statistics, data analysis, and programming, typically gained through coursework or relevant experience in computer science, mathematics, or related fields. Familiarity with tools such as Python or R, SQL databases, and data visualization libraries is highly valuable, and experience with machine learning platforms or certifications can be advantageous. Effective communication, problem-solving, and a collaborative mindset help you excel in team-oriented, fast-paced environments. These competencies are crucial for analyzing complex datasets, delivering actionable insights, and supporting business decision-making.

Is 30 too late for data science?

Data science Co Op roles often target students or early-career individuals, but age is not a strict barrier. Many professionals transition into data science later in their careers by acquiring relevant skills such as programming, statistics, and tools like Python or R, and completing certifications or projects to demonstrate expertise.

What is a Data Science Co Op job?

A Data Science Co-Op is a temporary, structured work experience program for students or early-career professionals to apply data science skills in a real-world setting. Co-Ops typically last several months and involve tasks such as data analysis, machine learning model development, and visualization. Participants work closely with data teams, gaining hands-on experience with tools like Python, SQL, and cloud platforms. Unlike internships, Co-Op positions may be full-time for a semester and often offer deeper engagement with projects. This experience helps build technical skills, industry knowledge, and professional connections for future career opportunities.

More about Data Science Co Op jobs
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What job categories do people searching Data Science Co Op jobs look for? The top searched job categories for Data Science Co Op jobs are:
Data Science Co Op jobs near you
Data Engineer - Operational Support (Co-op)

Data Engineer - Operational Support (Co-op)

Campbell Soup Company

Camden, NJ • On-site

$115K - $138K/yr

Full-time

Posted 17 days ago

Job description

Since 1869, we've connected people through food they love. We're proud to be stewards of amazing brands that people trust. Our portfolio includes the iconic Campbell's brand, as well as Cape Cod, Chunky, Goldfish, Kettle Brand, Lance, Late July, Pacific Foods, Pepperidge Farm, Prego, Pace, Rao's Homemade, Snack Factory, Snyder's of Hanover. Swanson, and V8.
Here, you will make a difference every day. You will be supported to build a rewarding career with opportunities to grow, innovate and inspire. Make history with us.
Operational Support Data Engineer (Co-op)
We are seeking a motivated and curious Data Engineer to join our Enterprise Data & Analytics team. This co-op provides hands-on experience building and supporting cloud-based data platforms and pipelines that power enterprise analytics, reporting, and AI/ML solutions.
You will work with tools such as Databricks, Snowflake, Azure, ADLS, ADF, Power BI, and SAP integrations in an Agile environment.
If you are passionate about data, cloud technologies, and solving complex problems, we want to hear from you.
Key Responsibilities
  • Build Data Pipelines: Develop and support scalable data pipelines and ETL/ELT workflows.
  • Data Ingestion & Integration: Ingest data from SAP, APIs, databases, flat files, and cloud platforms.
  • Data Transformation: Build transformations using Python, PySpark, and SQL.
  • Data Modeling & STTM: Support STTM, semantic layers, and data modeling for analytics.
  • Support Analytics & AI/ML: Prepare datasets for reporting, AI/ML, and advanced analytics.
  • Monitor & Troubleshoot: Track pipeline health and resolve failures, performance, and data quality issues.
  • Data Operations: Support incident triage, root cause analysis, and operational monitoring.
  • BI Collaboration: Support Power BI datasets, semantic models, and reporting solutions.
  • DevOps & CI/CD: Assist with deployments, testing, and automation.
  • Agile Delivery: Participate in sprint planning, stand-ups, and retrospectives.
  • Documentation: Create runbooks, designs, and technical documentation.
  • Automation & AI: Explore automation and AI-driven improvements.
  • Monitoring & Troubleshooting: Learn how to monitor platform health, data refreshes, workloads, and integrations; help investigate and troubleshoot failures or performance issues.
  • Incident & Problem Resolution:Support issue resolution by partnering with senior engineers to perform basic root-cause analysis and document fixes and learnings.

Learning & Development Opportunities
  • Hands-on experience with Databricks, Snowflake, Azure, ADLS, and ADF.
  • Exposure to ETL/ELT, data modeling, orchestration, and CI/CD.
  • Mentorship from Data, Platform, and AI/ML Engineers.
  • Experience working in Agile/Scrum and DevOps environments.
  • Exposure to enterprise use cases across supply chain, finance, reporting, and AI/ML.

Qualifications
  • Pursuing a degree in Computer Science, Data Engineering, Data Science, or related fields.
  • Basic knowledge of SQL and relational databases.
  • Programming in Python and/or PySpark.
  • Understanding of ETL/ELT, data modeling, or STTM concepts.
  • Familiarity with Databricks, Snowflake, Azure, ADF, ADLS, or Power BI is a plus.
  • Exposure to AI/ML, CI/CD, or DevOps is beneficial.
  • Strong problem-solving and analytical skills.
  • Strong communication and teamwork skills.
  • Self-motivated with a willingness to learn.

The Company is committed to providing equal opportunity for employees and qualified applicants in all aspects of the employment relationship, including consideration for employment, without regard to race, color, sex, sexual orientation, gender identity, national origin, citizenship, marital status, protected veteran status, disability, age, religion, or any other classification protected by law.

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