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Environmental Data Science Jobs in Arizona (NOW HIRING)

LPL Financial

Sr. Analyst, Data Science

Tempe, AZ · On-site

$85K - $143K/yr

From cutting-edge resources and a collaborative environment to the freedom to make an impact and ... This role is ideal for a data scientist who is equally comfortable writing code, building models ...

State Farm

Data Scientist

Tempe, AZ

Experience with gathering and interpreting business requirements for designing and scalable data science solutions in a regulatory environment (including but not limited to insurance, healthcare, and ...

onsemi

Sr. Manager AI & Data Science

Scottsdale, AZ · On-site

Sr. Manager AI & Data Science We are seeking a visionary and technically strong Senior Manager of ... Proven experience deploying AI/ML solutions in production environments. * Strong knowledge of cloud ...

State Farm

Data Scientist

Tempe, AZ · Hybrid

... environment. Why Join Our Data Science Team? At State Farm, we are dedicated to helping our team members develop to their full potential. As a Data Scientist, you have the unique opportunity to ...

onsemi

Sr. Manager AI & Data Science

Scottsdale, AZ

Proven experience deploying AI/ML solutions in production environments. * Strong knowledge of cloud ... Oversee data science project lifecycles, from ideation to production, ensuring alignment with ...

Koantek

Data Scientist

Chandler, AZ · On-site

Familiarity with cloud-based AI/ML environments. * Experience working in enterprise-scale AI initiatives. Experience Required: * 5+ years of experience in Data Science, Machine Learning, or AI ...

Koantek

Data Scientist

Chandler, AZ

Familiarity with cloud-based AI/ML environments. Experience working in enterprise-scale AI initiatives. Experience Required: 5+ years of experience in Data Science, Machine Learning, or AI-related ...

Oscar Health

Data Scientist II

Tempe, AZ · Hybrid

$131K - $172K/yr

Help ensure data science processes and outputs align with broader team strategies and roadmaps ... Experience deploying or supporting models in production environments

Republic Services

Data Scientist III

Phoenix, AZ · On-site

They apply analytical and data science methods to real world datasets to solve ongoing business ... Proficiency with cloud computing environments (e.g. AWS). * Proficiency with Snowflake ...

Republic Services

Data Scientist III

Phoenix, AZ

They apply analytical and data science methods to real world datasets to solve ongoing business ... Proficiency with cloud computing environments (e.g. AWS). * Proficiency with Snowflake ...

Republic Services

Data Scientist III

Phoenix, AZ

They apply analytical and data science methods to real world datasets to solve ongoing business ... Proficiency with cloud computing environments (e.g. AWS). * Proficiency with Snowflake ...

Oscar Health

Data Scientist II

Tempe, AZ · On-site

$131K - $172K/yr

Help ensure data science processes and outputs align with broader team strategies and roadmaps ... Experience deploying or supporting models in production environments This is an authentic Oscar ...

Oscar Health

Data Scientist II

Tempe, AZ · Hybrid

$131K - $172K/yr

Help ensure data science processes and outputs align with broader team strategies and roadmaps ... Experience deploying or supporting models in production environments This is an authentic Oscar ...

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All JobsEnvironmental Data Science JobsEnvironmental Data Science Jobs in Arizona

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 Jul 14, 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.

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.

Can data scientists make $300k?

Environmental data scientists can potentially earn $300,000 or more at senior levels or in specialized roles, especially with extensive experience, advanced skills in machine learning, and working in high-demand industries or organizations. However, such salaries are typically achieved through seniority, leadership positions, or in regions with higher compensation standards.

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.

Is 40 too late for data science?

Environmental Data Science is a field that values skills and experience over age, and many professionals transition into data science later in their careers. Gaining relevant knowledge in programming, statistics, and environmental data tools can enable a successful entry regardless of age, as continuous learning and practical experience are key factors in the field.

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 is the highest paying environmental science job?

Environmental Data Science roles such as senior environmental data scientists or environmental analytics managers tend to have the highest salaries in the field, often exceeding $100,000 annually. These positions typically require advanced skills in data analysis, programming, and environmental modeling, and may involve leadership responsibilities or specialized expertise in areas like climate modeling or sustainability analytics.

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:
What job categories do people searching Environmental Data Science jobs in Arizona look for? The top searched job categories for Environmental Data Science jobs in Arizona are:
Environmental Data Science jobs near you
Infographic showing various Environmental Data Science job openings in Arizona as of July 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $114,378 per year, or $55 per hour.
Vice President - Data Science

Vice President - Data Science

Caris Life Sciences

Tempe, AZ • On-site

Full-time

Posted 24 days ago

Job description

Job Summary:
Caris Life Sciences is transforming cancer care through precision medicine and innovative approaches. The Vice President, Data Science provides senior leadership for AI-driven clinical insights and predictive modeling initiatives, overseeing a multidisciplinary team and ensuring the delivery of impactful AI innovations.
Responsibilities:
• Define and execute the strategy for AI-driven clinical insight and molecular signature development across Caris’ molecular profiling platforms.
• Identify clinically relevant questions where advanced analytics can deliver prognostic or predictive insights.
• Oversee development of AI signatures integrating genomic, transcriptomic, proteomic, and clinical outcomes data.
• Establish governance and standards for model development, validation, documentation, and lifecycle management.
• Collaborate with Regulatory and Clinical Development teams to ensure appropriate validation and evidence generation.
• Lead implementation of AI products within a regulated CAP/CLIA clinical environment.
• Oversee engineering and production deployment of AI pipelines within Caris’ clinical reporting infrastructure.
• Ensure scalable, reproducible, auditable computational pipelines and canonical data models.
• Lead development of clinically interpretable reporting frameworks for physicians.
• Partner with Product and Commercial teams to integrate AI insights into clinical reports and decision-support tools.
• Build, mentor, and lead high-performing teams of data scientists and computational biologists.
• Set organizational goals, budgets, roadmaps, OKRs, and performance metrics aligned with corporate priorities.
• Champion a culture of scientific rigor, accountability, transparency, and continuous improvement.
Qualifications:
Required:
• PhD in Data Science, Biostatistics, Computer Science, Biomedical Engineering, or a related field.
• 10+ years of experience building and implementing supervised and unsupervised machine learning models for complex problem solving.
• Expert proficiency in Python (pandas, NumPy, statistical and ML libraries) and SQL.
• Strong expertise in machine learning, statistical modeling, and large-scale biomedical data analysis.
• Experience working with multi-omic datasets including genomics, transcriptomics, and proteomics.
• Experience leveraging large clinical datasets for biomarker discovery, predictive modeling, or outcomes research.
• Working knowledge of regulatory considerations for algorithm development in clinical diagnostics environments.
• Demonstrated people leadership and direct management experience with accountability for large-scale outcomes.
• Outstanding verbal and written communication skills.
• Proficient in Microsoft Office Suite including Word, Excel, Outlook, and PowerPoint.
• This is an onsite role based at our Phoenix, AZ office and requires regular in‑person presence.
Preferred:
• Experience working in regulated clinical laboratory environments (CAP/CLIA).
• Familiarity with cloud computing platforms and large-scale data infrastructures.
• Experience translating advanced analytics into physician-facing clinical products.
Company:
Caris Life Sciences develops molecular profiling and AI-driven technologies to support precision medicine in oncology. Founded in 2008, the company is headquartered in Irving, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

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