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Environmental Data Science Jobs in Arizona (NOW HIRING)

As a Senior AI / Data Science Engineer in the MDCE Data Science organization, you will play a ... Experience deploying AI/ML solutions into production environments. * Experience developing APIs and ...

Experience * 3- 5 years of experience in data science or advanced analytics, preferably in a high-tech manufacturing environment. Semiconductor equipment manufacturing experience is a definitive ...

We offer a competitive salary, generous benefits, unlimited growth potential, and a collegiate work environment. The People Data Scientist applies advanced statistical, analytical, and data science ...

We offer a competitive salary, generous benefits, unlimited growth potential, and a collegiate work environment. The People Data Scientist applies advanced statistical, analytical, and data science ...

We offer a competitive salary, generous benefits, unlimited growth potential, and a collegiate work environment. The People Data Scientist applies advanced statistical, analytical, and data science ...

Experience * 3- 5 years of experience in data science or advanced analytics, preferably in a high-tech manufacturing environment. Semiconductor equipment manufacturing experience is a definitive ...

Data Scientist

Scottsdale, AZ · On-site

$80K - $120K/yr

Collaborate with ML Engineering to productionize models on Azure Technical Environment (Azure AI/ML ... Master's degree in Data Science, CS, Statistics, Biomedical Informatics, or related field preferred ...

Perform analytics in cloud-based environments, support the development of clear leadership-ready presentations, and stay current on developments in data science, behavioral science, and adjacent ...

Environmental Scientist II

Phoenix, AZ · On-site

$87K - $120K/yr

Review and/or prepare and maintain detailed records and files of environmental data and ... Bachelor's degree in Environmental Science, Environmental Technology, Earth Science or related ...

Environmental Scientist II

Phoenix, AZ · On-site

$87K - $120K/yr

Review and/or prepare and maintain detailed records and files of environmental data and ... What You Bring To Freeport Bachelor's degree in Environmental Science, Environmental Technology ...

Senior Solutions Data Architect

Scottsdale, AZ

$68.75 - $91.75/hr

Supports Data Science team in the approach to implement advanced analytical models and supporting ... Experience with AWS frameworks, data tools and environment. * Understanding of data architecture ...

Showing results 21-40

Environmental Data Science information

See Arizona salary details

$34.9K

$114.4K

$183.1K

How much do environmental data science jobs pay per year?

As of Aug 6, 2026, the average yearly pay for environmental data science in Arizona is $114,378.00, according to ZipRecruiter salary data. Most workers in this role earn between $91,800.00 and $126,700.00 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 Arizona? The most popular types of Environmental Data Science jobs in Arizona are:
What are popular job titles related to Environmental Data Science jobs in Arizona? For Environmental Data Science jobs in Arizona, the most frequently searched job titles are:
Infographic showing various Environmental Data Science job openings in Arizona as of July 2026, with employment types broken down into 1% As Needed, 86% Full Time, 10% Part Time, 1% Temporary, and 2% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $114,378 per year, or $55 per hour.

Senior AI / Data Science Engineer

Intel Corporation

Phoenix, AZ • On-site

$105K - $143K/yr

Full-time

Medical, Retirement, PTO

Posted 6 days ago


Intel rating

8.7

Company rating: 8.7 out of 10

Based on 147 frontline employees who took The Breakroom Quiz

19th of 156 rated electronics manufacturers


Job description

Job Details:
Job Description:
Join Intel and build a better tomorrow.
Manufacturing Development Customer Engineering (MDCE) is Intel's newest organization within Intel Foundry Technology Manufacturing (FTM). We bridge the critical gap between Technology Development (TD) and High Volume Manufacturing (HVM), accelerating technology readiness, manufacturing maturity, yield improvement, and operational excellence across Intel's product and foundry ecosystem. MDCE partners across engineering organizations to transform manufacturing insights into scalable production solutions that enable Intel's foundry strategy and future growth.
As a Senior AI / Data Science Engineer in the MDCE Data Science organization, you will play a critical role in shaping the future of AI-driven semiconductor manufacturing. You will lead the development, deployment, and adoption of advanced Artificial Intelligence (AI), Machine Learning (ML), and Generative AI technologies that accelerate yield learning, improve process optimization, and increase engineering productivity across Intel Foundry.
The successful candidate will combine deep expertise in semiconductor manufacturing analytics, AI/ML methodologies, and software engineering with the ability to influence cross-functional stakeholders and drive innovation at scale.
Key Responsibilities:
  • Lead development of advanced AI, Machine Learning, and Generative AI solutions that address critical semiconductor manufacturing and yield challenges.
  • Drive adoption of AI technologies across MDCE and partner engineering organizations, enabling data-driven decision making and measurable business impact.
  • Develop and deploy Large Language Model (LLM) and Generative AI applications that improve engineering productivity, accelerate troubleshooting, and enhance knowledge discovery.
  • Analyze large-scale manufacturing datasets to identify yield detractors, process excursions, root causes, and optimization opportunities.
  • Design and implement scalable data pipelines, analytics frameworks, and AI infrastructure that enable robust and sustainable manufacturing analytics.
  • Collaborate closely with Yield Engineering, Process Integration, Manufacturing, and Technology Development teams to solve complex semiconductor challenges.
  • Establish best practices for AI model development, software quality, deployment, monitoring, and lifecycle management.
  • Lead cross-functional technical initiatives and influence strategic AI roadmaps across multiple engineering organizations.
  • Mentor engineers and contribute to the growth of Intel's technical AI and Data Science community.
  • Support Intel Foundry's manufacturing excellence objectives through innovative applications of AI, machine learning, and advanced analytics.

Core Competencies
  • Ability to collaborate effectively within a team setting.
  • Excellent Communication Skills.

Qualifications:
The Minimum qualifications are required to be initially considered for this position. Minimum qualifications listed below would be obtained through a combination of industry relevant job experience, internship experience and / or schoolwork/classes/research. The preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates.
Minimum Qualifications
  • Bachelor's degree in Computer Science, Data Science, Electrical Engineering, Industrial Engineering, Statistics, Applied Mathematics, or in a STEM-related field.
  • 6+ years of industry experience in one or more of the following: Data Science, Machine Learning, Artificial Intelligence, Advanced Analytics. Performing yield analysis, root-cause analysis, process engineering analytics, and Statistical Process Control (SPC).
  • 5+ Years of Semiconductor industry experience with manufacturing, process, and yield-related challenges.
  • Strong programming experience in Python and SQL including developing scalable data pipelines and production-quality analytical solutions.
  • Experience leading cross-functional technical projects and driving business impact through data-driven solutions.

Preferred Qualifications
  • Post graduate degree in Computer Science, Data Science, Electrical Engineering, Industrial Engineering, Statistics, Applied Mathematics, or in a STEM-related field.
  • Experience driving AI transformation initiatives across large engineering organizations.
  • Experience developing Generative AI applications using Retrieval Augmented Generation (RAG) and Agentic AI architectures.
  • Experience deploying AI/ML solutions into production environments.
  • Experience developing APIs and microservices.
  • Semiconductor foundry experience.
  • Background in Yield Engineering, Process Integration, Process Development, or Manufacturing Engineering.
  • Proven track record mentoring engineers and providing technical leadership

Job Type:
Experienced Hire
Shift:
Shift 1 (United States of America)
Primary Location:
US, Arizona, Phoenix
Additional Locations:
US, Oregon, Hillsboro
Posting Statement:
All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance.
Position of Trust
N/A
Benefits
We offer a total compensation package that ranks among the best in the industry. It consists of competitive pay, stock bonuses, and benefit programs which include health, retirement, and vacation. Find out more about the benefits of working at Intel.
Annual Salary Range for jobs which could be performed in the US: $136,900.00-269,150.00 USD
The range displayed on this job posting reflects the minimum and maximum target compensation for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific compensation range for your preferred location during the hiring process.
Work Model for this Role
This role will be eligible for our hybrid work model which allows employees to split their time between working on-site at their assigned Intel site and off-site. * Job posting details (such as work model, location or time type) are subject to change.
ADDITIONAL INFORMATION: Intel is committed to Responsible Business Alliance (RBA) compliance and ethical hiring practices. We do not charge any fees during our hiring process. Candidates should never be required to pay recruitment fees, medical examination fees, or any other charges as a condition of employment. If you are asked to pay any fees during our hiring process, please report this immediately to your recruiter.

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About Intel

Sourced by ZipRecruiter

Intel strives to make every facet of semiconductor manufacturing state-of-the-art -- from semiconductor process development and manufacturing, through yield improvement to packaging, final test and optimization, and world class Supply Chain and facilities support. Employees in the Technology and Manufacturing Group are part of a worldwide network of design, development, manufacturing, and assembly/test facilities, all focused on utilizing the power of Moore's Law to bring smart, connected devices to every person on Earth

Industry

Manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1968