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Internship Data Scientist Supply Chain Jobs (NOW HIRING)

Auger

Data Scientist - Supply Chain

Bellevue, WA · On-site

They are seeking a Data Scientist to transform raw customer data into structured insights, working closely with supply chain experts to develop AI and optimization systems for complex supply chain ...

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Internship Data Scientist Supply Chain information

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How much do internship data scientist supply chain jobs pay per year?

As of Sep 1, 2026, the average yearly pay for internship data scientist supply chain in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

What does an internship data scientist in supply chain do?

An Internship Data Scientist in Supply Chain works with data to help optimize and improve supply chain processes such as inventory management, demand forecasting, and logistics. They analyze large datasets, build predictive models, and create visualizations to support decision-making. Interns often collaborate with other teams to identify inefficiencies and recommend data-driven solutions, gaining practical experience in both data science and supply chain management.

What are the key skills and qualifications needed to thrive as an internship data scientist in supply chain?

To thrive as an Internship Data Scientist in Supply Chain, you need strong analytical skills, knowledge of statistics, and familiarity with supply chain concepts, typically supported by coursework in data science or related fields. Proficiency with tools like Python, SQL, and data visualization platforms, as well as experience with machine learning frameworks, is highly valuable. Effective communication, problem-solving abilities, and a collaborative mindset help you interpret data insights and work well with cross-functional teams. These skills and qualities are crucial for generating actionable insights that optimize supply chain processes and drive business improvements.

What types of projects might I work on as an internship data scientist in supply chain?

As a Data Scientist intern in a supply chain setting, you can expect to work on projects such as demand forecasting, inventory optimization, and predictive analytics to enhance operational efficiency. Your daily responsibilities may include data cleaning, building statistical models, and collaborating with supply chain analysts and operations teams to interpret results. You’ll often use tools like Python, SQL, and data visualization platforms, gaining experience in both technical and business aspects of supply chain management. These projects provide valuable exposure to solving real-world logistics challenges and offer great learning opportunities for those interested in data-driven decision-making.
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Internship Data Scientist Supply Chain jobs near you
Infographic showing various Internship Data Scientist Supply Chain job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $165,018 per year, or $79.3 per hour.

Data Scientist - Supply Chain

Auger

Bellevue, WA • On-site

Full-time

Re-posted 18 days ago

Job description

Job Summary:
Auger is an autonomous operating system for supply chains that integrates various enterprise systems into a single data layer. They are seeking a Data Scientist to transform raw customer data into structured insights, working closely with supply chain experts to develop AI and optimization systems for complex supply chain challenges.
Responsibilities:
• Understand how customer businesses actually operate: how work flows, where decisions are made, and what good looks like operationally.
• Interpret customer data and assign context — figure out what the data means, how entities relate, and where the gaps and inconsistencies are.
• Form and test hypotheses using data to prove or disprove ideas about the system and the relationships between entities within it.
• Build inference techniques and regression models that extract signal and quantify relationships.
• Translate business logic and objectives into mathematical constraints and quantifiable calculations.
• Identify missing concepts needed to close process and data loops — spot what isn't there yet but needs to be.
• Serve as the critical link between applied science and data engineering: translate scientific requirements into engineering specifications and vice versa.
Qualifications:
Required:
• Master's degree in Data Science, Statistics, Applied Mathematics, or a related quantitative field; undergraduate degree in Engineering, Mathematics, Economics, or Computer Science.
• Strong proficiency in Python and SQL; comfortable working with large, messy, real-world datasets.
• Experience with machine learning and optimization models, with strong statistical intuition — you notice when results look wrong and can articulate why.
• Enough familiarity with data pipelines and infrastructure to have productive technical conversations with data engineers.
• Sharp analytical instincts paired with strong common sense: you can tell when something doesn't add up, and you use data to prove or disprove it.
• A builder's mindset — you break problems into testable components, take things apart, and improve them.
• Comfort with ambiguity and a bias toward asking the right question before assuming the right answer.
Preferred:
• Supply chain and logistics experience is ideal.
• Hands-on experience with any complex, interrelated physical system is highly beneficial.
Company:
Auger is a logistics software startup that integrates with inventory management systems to provide insights for supply chain businesses. Founded in 2024, the company is headquartered in Bellevue, USA, with a team of 51-200 employees. The company is currently Growth Stage.

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