1

Environmental Data Science Jobs in Iowa (NOW HIRING)

Qualifications 2+ years of hands‐on experience in a quantitative role or research environment -- such as data science, statistics, economics, finance, physics, biology, epidemiology, operations ...

Environmental Scientist/Geologist

Des Moines, IA

$73.20K - $96.10K/yr

Bachelor's degree in Environmental Science, Geology, Hydrogeology, or related field * Experience with field sampling methods and related data management and reporting * Experience working with ...

Bachelor's degree in Environmental Science, Geology, Hydrogeology, or related field * Experience with field sampling methods and related data management and reporting * Experience working with ...

Environmental Scientist/Geologist

Cedar Rapids, IA

$73.40K - $96.40K/yr

Bachelor's degree in Environmental Science, Geology, Hydrogeology, or related field * Experience with field sampling methods and related data management and reporting * Experience working with ...

Manage multiple projects in a fast-paced, collaborative environment. Core Skills & Qualifications * Bachelor's degree in Data Analytics or a related field. * 25 years of experience in data science ...

New

Collect environmental data and conduct sampling and inspections required to complete regulatory ... Bachelor's degree in Environmental Science, Natural Sciences, Environmental Engineering, or a ...

Decision Scientist

Nevada, IA · On-site +1

$40/hr

Qualifications 2+ years of hands‐on experience in a quantitative role or research environment -- such as data science, statistics, economics, finance, physics, biology, epidemiology, operations ...

Comfort working in UNIX-based environments using command-line tools * Ability to communicate complex data science concepts thoughtfully and inclusively to a wide range of stakeholders Preferred

next page

Showing results 1-20

Environmental Data Science information

See Iowa salary details

$35.2K

$115.3K

$184.6K

How much do environmental data science jobs pay per year?

As of May 29, 2026, the average yearly pay for environmental data science in Iowa is $115,284.00, according to ZipRecruiter salary data. Most workers in this role earn between $92,500.00 and $127,700.00 per year, depending on experience, location, and employer.

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

To thrive as an Environmental Data Scientist, you need strong quantitative skills, expertise in environmental science, and a relevant degree in data science, statistics, or a related field. Familiarity with data analysis tools such as Python, R, GIS software, and experience with large datasets or machine learning techniques is typical. Exceptional problem-solving abilities, communication skills, and attention to detail set top performers apart in this field. These competencies are crucial for effectively interpreting complex environmental data, informing policy, and driving impactful sustainability initiatives.

What are some common challenges faced by environmental data scientists when working with real-world datasets?

Environmental data scientists often encounter challenges such as incomplete or inconsistent data, varying data formats, and the need to integrate information from multiple sources like sensors, satellites, and field observations. Addressing missing values, data quality issues, and ensuring proper geospatial alignment can be time-consuming but is essential for producing reliable analyses. Collaboration with domain experts and stakeholders is frequently required to interpret findings and ensure that the results are actionable for environmental policy or management decisions.

What is Environmental Data Science?

Environmental Data Science is an interdisciplinary field that uses statistical, computational, and analytical techniques to collect, analyze, and interpret large sets of data related to the environment. Professionals in this field work on issues like climate change, pollution, biodiversity, and natural resource management by extracting meaningful insights from complex environmental datasets. Their work supports decision-making for policy, conservation, and sustainability initiatives. Environmental data scientists often collaborate with ecologists, geographers, and policymakers to address environmental challenges using data-driven approaches.

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

AspectEnvironmental Data ScienceEnvironmental Data Analyst
Required CredentialsTypically requires a degree in data science, environmental science, or related fields; often includes programming and statistical certificationsUsually requires a degree in environmental science, geography, or related fields; may include basic data analysis certifications
Work EnvironmentResearch labs, data centers, environmental agencies, or consulting firmsEnvironmental agencies, research organizations, or consulting firms
Employer & Industry UsageUsed in environmental research, climate modeling, and policy analysisUsed in environmental monitoring, reporting, and data interpretation

Environmental Data Science focuses on developing models and algorithms to analyze complex environmental data, often requiring advanced programming skills. In contrast, Environmental Data Analysts primarily interpret and visualize environmental data to support decision-making. Both roles are vital but differ in technical depth and scope.

Infographic showing various Environmental Data Science job openings in Iowa as of May 2026, with employment types broken down into 72% Full Time, 21% Part Time, and 7% Contract. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution, with an average salary of $115,284 per year, or $55.4 per hour.
Data Science Consultant

Data Science Consultant

DataAnnotation

Nevada, IA • On-site, Remote

$40/hr

Full-time

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


Job description

Join the DataAnnotation team and contribute to developing cutting-edge AI systems, while enjoying the flexibility of remote work and setting your own schedule. We are looking for experienced quantitative professionals to help advance AI development. AI models are increasingly capable of performing complex analytical and scientific reasoning — but these systems still need practitioners with real-world quantitative experience to validate whether the outputs actually hold up in practice.

That's where you come in. As a member of DataAnnotation's team, you'll work closely with state-of-the-art AI models on tasks like evaluating AI-generated quantitative analysis, solving technical problems, and providing feedback that directly shapes how these systems reason about data, models, and scientific problems. Whether your background is in data science, astrophysics, economics, biostatistics, operations research, or any other quantitative field, if you think rigorously about data and models, your skills are directly applicable here.

Some team members fit this work alongside a full-time role, while others treat it as their primary focus. To get started, once you sign up for an account, you'll take a short assessment (this serves as our version of an interview). If you pass, you'll receive an email confirmation, and paid work will become available on our platform.

Benefits Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New Zealand. Flexible schedule: choose which projects you take on and when you work. Competitive pay: projects are paid hourly, starting at $40+ USD per hour.

Impact: help shape the future of AI systems built to reason about data and analytics. Responsibilities Evaluate AI-generated quantitative work, including statistical analysis, predictive modeling, scientific reasoning, and data-driven insights, for technical accuracy and real-world validity. Design and solve quantitative problems used to train and benchmark AI systems, spanning areas like forecasting, experimental analysis, optimization, and statistical inference.

Write clear technical explanations and well-documented analytical code. Provide feedback that directly shapes the next generation of AI models built for quantitative reasoning. Qualifications 2+ years of hands‐on experience in a quantitative role or research environment — such as data science, statistics, economics, finance, physics, biology, epidemiology, operations research, or any adjacent field.

Some coding experience required, with comfort writing and reviewing analytical code end-to-end. Practical experience with statistical methods, predictive modeling, and experiment design (e.g., A/B testing, hypothesis testing, regression, classification, time‐series forecasting). Fluency in English (native or bilingual level) with strong writing skills.

A bachelor's degree in a quantitative field is preferred (Statistics, Computer Science, Mathematics, Engineering, or similar); a master's or PhD is a plus. Relevant credentials are a plus (e.g., Kaggle Competition ranking, AWS/GCP ML certifications, or equivalent demonstrated expertise). Note: Payment is made via PayPal.

We will never ask for any money from you. This job is only available to those in the US, Canada, UK, Ireland, Australia, and New Zealand. #datascience #J-18808-Ljbffr