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Environmental Data Science Jobs in Chicago, IL (NOW HIRING)

... the Databricks environment. Sitting within our Analytics + Technology (A+T) team, this role ... They will work under the guidance of senior data science leaders to deliver impactful, data-driven ...

... the Databricks environment. Sitting within our Analytics + Technology (A+T) team, this role ... They will work under the guidance of senior data science leaders to deliver impactful, data-driven ...

The team is responsible for protecting existing global data science environments, modernizing data science by onboarding practitioners to One True and cloudbased tooling, and continuously enhancing ...

The team is responsible for protecting existing global data science environments, modernizing data science by onboarding practitioners to One True and cloudbased tooling, and continuously enhancing ...

Data Scientist

Chicago, IL · On-site

$110 - $160/hr

Exposure to enterprise-scale data science and machine learning projects. * Collaborative and innovation-driven work environment. * Competitive compensation package. * Long-term career growth and ...

New

Sr. Data Scientist

Chicago, IL · Remote

$85 - $100/hr

Translate business problems in a variety of business areas into well-defined data science projects ... Experience operating in an Agile Methodology environment. * Experience with DevOps and CI/CD ...

In this position, your data science expertise will help us build new features and improve our ... an agile environment. What you bring to the team: * Partner with stakeholders across the ...

In this position, your data science expertise will help us build new features and improve our ... an agile environment. What you bring to the team: * Partner with stakeholders across the ...

... Data Science Lab prototypes are engineered for full production environments • Work across multiple projects in a fluid environment where work is required across the full research lifecycle from ...

Data Science is a driver of significant competitive advantage for Kemper and is critical to the ... Exposure to cloud platforms such as AWS, Azure, Databricks, or similar environments. * Exposure to ...

Experience with AWS, SageMaker, or similar cloud-based data science environments. * Experience supporting BI outputs in Tableau, Power BI, Looker, or similar tools. * Familiarity with MLOps best ...

Showing results 21-40

Environmental Data Science information

See Chicago, IL salary details

$38.6K

$126.4K

$202.4K

How much do environmental data science jobs pay per year?

As of Aug 10, 2026, the average yearly pay for environmental data science in Chicago, IL is $126,438.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $140,100.00 per year, depending on experience, location, and employer.

Is environmental data science a good major?

Environmental data science is a strong major for those interested in analyzing environmental data, using tools like GIS and statistical software. It prepares students for roles in environmental monitoring, research, and policy, often requiring skills in programming, data analysis, and environmental science. Job prospects are growing as organizations seek data-driven solutions to environmental challenges.

What does an environmental data scientist do?

An environmental data scientist analyzes environmental data to identify patterns, assess environmental risks, and support decision-making. They use statistical tools, programming languages like Python or R, and GIS software to interpret data related to climate, pollution, and natural resources, often working with large datasets and models to inform environmental policies and practices.

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 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 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.

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 the most commonly searched types of Environmental Data Science jobs in Chicago, IL? The most popular types of Environmental Data Science jobs in Chicago, IL are:
What job categories do people searching Environmental Data Science jobs in Chicago, IL look for? The top searched job categories for Environmental Data Science jobs in Chicago, IL are:
Infographic showing various Environmental Data Science job openings in Chicago, IL as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $126,438 per year, or $60.8 per hour.

Staff Data Scientist & AI Researcher

The University of Chicago

Chicago, IL • On-site

Full-time

Medical, Retirement, PTO

Re-posted yesterday


University Of Chicago rating

8.1

Company rating: 8.1 out of 10

Based on 47 frontline employees who took The Breakroom Quiz

160th of 617 rated colleges and universities


Job description

Department
BSD CTD - Data Science
About the Department
The Center for Translational Data Science (CTDS) at the University of Chicago is a research center whose mission is to develop the discipline of translational data science to impactful problems in biology, medicine, healthcare, and the environment. We envision a world in which researchers have ready access to the data needed and the tools required to make data driven discoveries that increase our scientific knowledge and improve the quality of life. We architect ecosystems of large-scale commons of research data, computing resources, applications, tools, and services for the broader research community to use data at scale to pursue scientific inquiry and accelerate discovery. Learn more at https://gdc.cancer.gov/ https://gen3.org/ https://stats.gen3.org/ and https://ctds.uchicago.edu/.
Job Summary
The Center for Translational Data Science at the University of Chicago is seeking a Staff Data Scientist to support a diverse range of research projects. Data Scientists work in a collaborative interdisciplinary team and play a critical role in AI/ML tooling, features, and improvements for our open-source software systems and applications, analyzing data, and in understanding and representing user requirements to internal and external stakeholders in our translational data science projects and products. Under the leadership of team or project leads, a person in this position will be a key contributor to the design and implementation of algorithms, AI/ML models, and workflows to enable the discovery of valuable information in large volumes of data from various sources; organizes, harmonizes, and analyzes data sets and develops tools to assist such processes; uses various technologies to visualize data or enable data visualization; and creates applications of general value to the project and product owners. The job uses best practices and advanced knowledge of data manipulation, statistical applications, programming, analysis and modeling in order to implement projects related to the University's various internal data systems as well as from external sources.
This at-will position is wholly or partially funded by contractual grant funding which is renewed under provisions set by the grantor of the contract. Employment will be contingent upon the continued receipt of these grant funds and satisfactory job performance.
Responsibilities
  • Leading the Interpretation of data from multiple sources.
  • Developing and implementing software programs and services, software notebooks and software scripts for data transformation, data integration, data analysis and data visualization.
  • Building, validating and evaluating AI/ML models.
  • Contributing to and taking a leadership role in the enhancement and maintenance of previously developed in-house open-source data platforms, systems, applications and notebooks.
  • Performing various types of analysis involving multiple data sets.
  • Leading data science projects and initiatives within purview, by relaying data analysis and model deployment best practices, enhancing the technical knowledge of peers, and helping develop data science skills in junior employees and interns.
  • Leading the conceptualization, design, and execution of sophisticated data science projects and AI/ML solutions for research and production environments.
  • Establish and enforce data governance, quality assurance processes, and operational protocols for large, complex data sets from internal and external sources.
  • Assisting in providing leadership for design of user-facing computational resources.
  • Serving as a reference for staff, faculty members, and Gen3 users as a technical subject matter expert by applying principles of data science to define and scope data science projects that involve developing computational tools and services for data engineering, data manipulation, statistical analysis, and modeling.
  • Collaborating closely with faculty, researchers, and stakeholders to translate scientific and user requirements into actionable data science strategies and solutions.
  • Stay current with developments in data science, machine learning, artificial intelligence, and related fields, and adopt new methods and technologies to advance research goals.
  • Communicate complex technical concepts and project results clearly to technical and non-technical audiences, and present findings at internal and external forums.
  • Has a deep understanding of methods to analyze complex data sets for the purpose of extracting and purposefully using applicable information. May develop and maintain infrastructure that connects data sets.
  • Guides staff or faculty members in defining the project and applies principals of data science in manipulation, statistical applications, programming, analysis and modeling.
  • Calibrates data between large and complex research and administrative datasets. Guides and may set the operational protocols for collecting and analyzing information from the University's various internal data systems as well as from external sources.
  • Performs other related work as needed.

Minimum Qualifications
Education:
Minimum requirements include a college or university degree in related field.
Work Experience:
Minimum requirements include knowledge and skills developed through 5-7 years of work experience in a related job discipline.
Certifications:
---
Preferred Qualifications
Education:
  • Advanced degree in Computer Science, Data Science, Statistics, Mathematics, Bioinformatics, or a relevant quantitative field.

Experience:
  • Experience working in data science roles, preferably in an academic, research, or health/science environment.
  • Experience with collaborative open-source projects and software engineering best practices.
  • Experience working in multi-disciplinary academic teams.
  • Knowledge of biomedical and translational research data sources is a significant advantage.
  • Knowledge of hardware specifications required for AI/ML research and projecting resource needs and use in public clouds environments like AWS and GCP.
  • Knowledge of and experience with data and applications of interest to CTDS, including, but not necessarily limited to, AI data commons, AI data meshes, Gen3, NCI Genomic Data Commons, cancer genomics, biomedical imaging data, human clinical data.
  • Expertise in designing and implementing machine learning, deep learning, and statistical models for research and production.
  • Experience with biomedical data.
  • Experience collaborating on manuscripts and submitting papers for peer-reviewed, scientific publications.

Preferred Competencies
  • Advanced skills in problem solving and quantitative/qualitative analysis.
  • Able to organize and prioritize work assignments to meet project needs and work independently to identify and address needs beyond assigned tasks.
  • Strong communication skills to effectively convey complex findings while serving as a reference and subject matter expert for staff, faculty members, and Gen3 users.
  • Ability to quickly comprehend requirements and assignments and then explain his/her solutions in both writing and speech.
  • Ability to learn new skills quickly and manage complex projects.
  • Proficiency in Python, R, and other relevant programming languages; experience with open-source data science platforms, technologies, and cloud environments.
  • Outstanding analytical, problem-solving, and project management abilities.
  • Proven track record mentoring and leading project teams and communicating technical issues to diverse audiences.
  • Excellent written and verbal communication skills.

Working Conditions
  • Hybrid office/remote.

Application Documents
  • Resume/CV (required)
  • Cover Letter (preferred)

The University of Chicago uses AI-assisted tools to streamline and augment some recruitment processes; however, AI is not used to make hiring decisions.
When applying, the document(s) MUST be uploaded via the My Experience page, in the section titled Application Documents of the application.
Job Family
Research
Role Impact
Individual Contributor
Scheduled Weekly Hours
40
Drug Test Required
No
Health Screen Required
No
Motor Vehicle Record Inquiry Required
No
Pay Rate Type
Salary
FLSA Status
Exempt
Pay Range
$90,000.00 - $120,000.00
The included pay rate or range represents the University's good faith estimate of the possible compensation offer for this role at the time of posting.
Benefits Eligible
Yes
The University of Chicago offers a wide range of benefits programs and resources for eligible employees, including health, retirement, and paid time off. Information about the benefit offerings can be found in the Benefits Guidebook.
Posting Statement
The University of Chicago is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender, gender identity, or expression, national or ethnic origin, shared ancestry, age, status as an individual with a disability, military or veteran status, genetic information, or other protected classes under the law. For additional information please see the University's Notice of Nondiscrimination.
Job seekers in need of a reasonable accommodation to complete the application process should call 773-702-5800 or submit a request via Applicant Inquiry Form.
All offers of employment are contingent upon a background check that includes a review of conviction history. A conviction does not automatically preclude University employment. Rather, the University considers conviction information on a case-by-case basis and assesses the nature of the offense, the circumstances surrounding it, the proximity in time of the conviction, and its relevance to the position.
The University of Chicago's Annual Security & Fire Safety Report (Report) provides information about University offices and programs that provide safety support, crime and fire statistics, emergency response and communications plans, and other policies and information. The Report can be accessed online at: http://securityreport.uchicago.edu. Paper copies of the Report are available, upon request, from the University of Chicago Police Department, 850 E. 61st Street, Chicago, IL 60637.

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