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Environmental Data Science Intern Jobs in Minnesota

Unilever

Data Science Manager

Minneapolis, MN

Proven experience leading data science teams working on complex analytics initiatives in a commercial or product-driven environment. Strong background in data science modelling, with deep expertise ...

Whiterabbit.ai

As a Research Scientist Intern at Whiterabbit.ai, you will: * Play a key role in architecting the ... Large scale machine learning experience working with terabytes of data * Implemented custom ...

IWCO Direct

Data Science Operations Analyst

Chanhassen, MN · On-site

$90K - $95K/yr

The Data Science Operations Analyst plays a key role in supporting data-driven direct marketing ... Ability to manage multiple priorities in a fast-paced, production-oriented environment * Curiosity ...

Whiterabbit.ai

As a Research Scientist Intern at Whiterabbit.ai, you will: * Play a key role in architecting the ... Large scale machine learning experience working with terabytes of data * Implemented custom ...

Whiterabbit.ai

As a Research Scientist Intern at Whiterabbit.ai, you will: * Play a key role in architecting the ... Large scale machine learning experience working with terabytes of data * Implemented custom ...

Whiterabbit.ai

As a Research Scientist Intern at Whiterabbit.ai, you will: * Play a key role in architecting the ... Large scale machine learning experience working with terabytes of data * Implemented custom ...

Whiterabbit.ai

As a Research Scientist Intern at Whiterabbit.ai, you will: * Play a key role in architecting the ... Large scale machine learning experience working with terabytes of data * Implemented custom ...

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Environmental Data Science Intern information

What is the difference between Environmental Data Science Intern vs Environmental Data Analyst?

AspectEnvironmental Data Science InternEnvironmental Data Analyst
Required CredentialsTypically pursuing or recent graduate in environmental science, data science, or related fieldsBachelor's or master's in environmental science, data analysis, or related fields; some roles prefer certifications in data analysis
Work EnvironmentInternship setting, often in research labs, environmental agencies, or consulting firmsFull-time role in environmental agencies, consulting firms, or corporate sustainability teams
Employer & Industry UsageUsed by organizations offering internships to train future professionalsUsed by organizations analyzing environmental data for decision-making and reporting

The main difference is that an Environmental Data Science Intern is an entry-level position aimed at gaining experience, while an Environmental Data Analyst is a more experienced role focused on analyzing and interpreting environmental data to support organizational goals.

What types of projects do Environmental Data Science Interns typically work on, and how do they contribute to the overall team goals?

Environmental Data Science Interns often work on projects involving the collection, analysis, and visualization of environmental data, such as air or water quality, climate trends, or biodiversity metrics. Interns may assist in developing models to forecast environmental changes or create dashboards that help communicate findings to stakeholders. These tasks support the team's efforts in research, policy-making, or environmental management by providing actionable insights and ensuring data-driven decision-making. Collaboration with scientists, data engineers, and policy analysts is common, offering interns exposure to interdisciplinary teamwork.

What are the key skills and qualifications needed to thrive as an Environmental Data Science Intern, and why are they important?

To thrive as an Environmental Data Science Intern, you need a strong background in environmental science, statistics, and data analysis, typically supported by coursework or a degree in a related field. Familiarity with programming languages like Python or R, data visualization tools, and GIS software is often required. Attention to detail, problem-solving abilities, and effective communication skills help interns translate data into actionable insights and collaborate with multidisciplinary teams. These skills ensure that data-driven decisions can be made to address complex environmental challenges.

What is an Environmental Data Science Intern?

An Environmental Data Science Intern is a student or recent graduate who assists in analyzing environmental data to address issues such as climate change, pollution, or resource management. They use statistical methods, programming, and data visualization tools to process and interpret large datasets from sources like sensors, satellites, or field surveys. The role often involves working with environmental scientists to support research and inform decision-making. Interns gain hands-on experience in applying data science techniques to real-world environmental challenges, which can help prepare them for future careers in environmental science and analytics.
What are popular job titles related to Environmental Data Science Intern jobs in Minnesota? For Environmental Data Science Intern jobs in Minnesota, the most frequently searched job titles are:
What job categories do people searching Environmental Data Science Intern jobs in Minnesota look for? The top searched job categories for Environmental Data Science Intern jobs in Minnesota are:
What cities in Minnesota are hiring for Environmental Data Science Intern jobs? Cities in Minnesota with the most Environmental Data Science Intern job openings:
Environmental Data Science Intern jobs near you
Infographic showing various Environmental Data Science Intern job openings in Minnesota as of July 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, 1% Temporary, and 3% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution.

Data Science

Cloud think technologies LLC

Minneapolis, MN • On-site

Contractor

Posted 23 days ago

Job description

Data Science: We are interested in individuals who are adept at tackling undefined business problems using both traditional machine learning approaches and the latest generative AI techniques. Ideal candidates should have robust analytical skills and be proficient in Python coding. Moreover, they should be capable of working both independently and collaboratively with the rest of the team. Additionally, experience in document processing with various forms is highly preferred. Effective communication skills are also essential for this role.

AI Engineering:

Primary Responsibilities:

o Design and implement the systems to power modern web applications that enables users to derive information from patient data in a scalable, reliable, and cost-effective manner

o Ensure the delivery of high-quality, maintainable, and efficient code

o Be an advocate for product quality, including agile SCRUM methodologies, unit tests, code reviews and engineering specifications.

Required Qualifications

• BS Degree in Computer Science or equivalent

• 6+ years of hands-on software engineering design and programming experience

• Hands on experience in delivering at least two modern web applications, from design to implementation, test and release.

• Master the fundamentals of technologies such as HTTP protocols, REST API, Security Fundamentals: Encryption, Hashing, Web Security Development, Authentication and Authorization

• 3+ years hands on experience with Python programming

• Basic understanding of front-end development with React

• Understand performance issues and how to optimize database queries and caching methodologies

• Ability to debug complex software and system issues

• Improve team engineering excellence by leading clear documentation, troubleshooting, logging and applying engineering best practices.

• Quality mindset with unit and integration tests

• Extensive experience in Agile and Scrum. You know how to work within teams against a backlog, and how to enable true CI/CD. You understand the role of a Software Engineer in an Agile environment – where clarifying the solution approach, possessing deep understanding of product requirements and always watching for edge cases are paramount

• Knowledge spans the full stack, from deployment ops and database technologies through to front-end frameworks. Ideally, you have a deep understanding of both OOP and Functional stacks, Relational and NoSQL Data Stores, Streaming Applications and system development/maintenance in accloud platform such as AWS, gcp or Azure. (AWS a bonus!)

Nice-to-have Skills:

• Familiarity with OpenAPI / Swagger specifications

• Deployment experience: GitHub actions, Terraform, Docker, etc.

• AWS experience such as RDS, ALB, Redis Cache, Secret Manager, EC2, IAM