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Environmental Data Science Intern Jobs (NOW HIRING)

Tencent

Data Science Intern

Palo Alto, CA · On-site +1

$28.27 - $60/hr

A passion for applying mathematical models and computer science technology to data-driven decision ... We foster an environment where every employee of Tencent feels supported and inspired to achieve ...

Cresta

Data Science Intern (Customer Success)

We are looking for a motivated Data Science Intern to join our team. This role offers hands-on ... environment. What We're Looking For: * Enrolled in a Bachelor's or Master's degree program in ...

Evolver

Applied Data Science Intern

Palo Alto, CA · On-site

... startup environment. Program Details: Evolver is launching a small, highly selective summer internship cohort for students and emerging talent to gain hands-on experience applying data science ...

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How much do environmental data science intern jobs pay per hour?

As of Jun 5, 2026, the average hourly pay for environmental data science intern in the United States is $22.50, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $24.52 per hour, depending on experience, location, and employer.

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 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 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 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.

More about Environmental Data Science Intern jobs
What cities are hiring for Environmental Data Science Intern jobs? Cities with the most Environmental Data Science Intern job openings:
What are the most commonly searched types of Environmental Data Science jobs? The most popular types of Environmental Data Science jobs are:
What states have the most Environmental Data Science Intern jobs? States with the most job openings for Environmental Data Science Intern jobs include:
What job categories do people searching Environmental Data Science Intern jobs look for? The top searched job categories for Environmental Data Science Intern jobs are:
Environmental Data Science Intern jobs near you
Infographic showing various Environmental Data Science Intern job openings in the United States as of May 2026, with employment types broken down into 1% Internship, 2% As Needed, 68% Full Time, 22% Part Time, 1% Temporary, and 6% Contract. Highlights an 95% Physical, 2% Hybrid, and 3% Remote job distribution, with an average salary of $46,809 per year, or $22.5 per hour.
Data Science Intern (Summer 2026)

Data Science Intern (Summer 2026)

J&J Family of Companies

New Brunswick, NJ • On-site

$25.50 - $33/hr

Other

Medical

This job post has expired today. Applications are no longer accepted.

Job description

At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn more at jnj.com (https://www.jnj.com.) .

As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world. We provide an inclusive work environment where each person is considered as an individual. At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit.

Job Function:

Career Programs

Job Sub Function:

Non-LDP Intern/Co-Op

Job Category:

Career Program

All Job Posting Locations:

New Brunswick, New Jersey, United States of America

Job Description:

Data Science Intern – Global Finance Data Science

Johnson & Johnson

Position Summary

Join Johnson & Johnson’s Global Finance Data Science team to build production-minded analytics and AI solutions at enterprise scale. You will work with a global team of Data Scientists, Data Engineers, Finance Analysts, and ML Engineers to advance the data science and AI roadmap for Global Finance: delivering predictive insights, automation that reduces manual workload, and interactive decision-support experiences.

You will contribute across the solution lifecycle: problem framing, proof-of-concept, development, deployment, and adoption. Ensuring the right level of automation, integration, and governance for real-world use.

Key Responsibilities:

1, Predictive Analytics & Decision Support (50%)

  • Develop and evaluate statistical/ML models for financial forecasting and decision support (e.g., time series, supervised learning).

  • Engineer features and datasets from large enterprise sources; apply rigorous validation and error analysis.

  • Communicate results with clear business context; translate insights into actions and measurable outcomes.

  1. AI-Driven Process Improvement & Automation (20%)

  • Design and prototype AI-enabled process improvements, including targeted Generative AI use cases.

  • Build repeatable workflows (automation/orchestration as applicable) and contribute to scalable integration patterns.

  • Apply engineering discipline: version control, reproducible pipelines, documentation, and basic monitoring metrics.

  1. Reporting & Interactive Analytics (20%)

  • Develop interactive dashboards and analytics products (Power BI/Tableau) and/or lightweight apps (Dash/Streamlit).

  • Partner with stakeholders to define requirements, iterate quickly, and drive adoption through usability-focused design.

  1. Governance & Operational Excellence (5%)
  • Support documentation, model/run governance, and operational performance tracking for deployed solutions.
  1. Team & Development (5%)
  • Provide concise status updates, participate in team ceremonies, and actively learn the team’s standards and tooling.

Minimum Qualifications:

  • Pursuing a BS/MS in a quantitative discipline (e.g., CS, DS, Statistics, Engineering, Economics/Finance, Operations Research).

  • Strong Python proficiency with evidence of clean, structured code (projects, research, internships, or competitions).

  • Strong SQL skills and comfort working with large datasets (joins, aggregations, window functions preferred).

  • Solid foundations in statistics and machine learning; ability to explain modeling choices, assumptions, and trade-offs.

  • Strong communication skills: can present complex analysis clearly to technical and non-technical stakeholders.

  • An equivalent cumulative GPA of 3.0 or higher

  • Authorization to work in the United States on a permanent, full-time basis is required

Preferred Qualifications:

  • Experience taking a model from notebook → reproducible pipeline (packaging, tests, CI/CD concepts, or workflow tooling).

  • Exposure to cloud/data science platforms (e.g., AWS, Domino) and scalable compute patterns.

  • Experience with one or more: time-series forecasting, NLP, or experimentation/causal inference.

  • Built interactive analytics products end-to-end (Power BI/Tableau dashboards and/or Dash/Streamlit apps).

  • Familiarity with workflow automation tooling (e.g., Alteryx) and/or orchestration concepts.

  • Demonstrated ability to operate in ambiguity, drive clarity with stakeholders, and deliver measurable impact.

The anticipated base pay for this position is between $25.50/hour and $33/hour, but will be based on candidate’s program year, discipline, degree and/or experience.

This position is overtime eligible.

Co-Ops/Interns may be eligible to participate in Company employee benefit programs such as medical insurance, sick time, and holiday pay in accordance with the terms of the applicable plans.

For additional general information on Company benefits, please go to: - https://www.careers.jnj.com/employee-benefits

Ineligibility for severance.

Required Skills:

Preferred Skills:

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