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Geospatial Data Science Jobs in Arizona (NOW HIRING)

GIS Developer

Phoenix, AZ · On-site

$44/hr

These tools directly support internal operations and serve the citizens of Arizona by enabling data ... ArcGIS Pro knowledge: basic geospatial analysis, basic editing, and basic cartographic design

Water Resources Engineer

Phoenix, AZ · On-site

$100K - $135K/yr

Collect, evaluate, and present data in technical reports and oral presentations. * Assist in the ... Bachelor's of Science in Civil Engineering * Master's degree in with an emphasis in Hydrology and ...

Collect, evaluate, and present data in technical reports and oral presentations. * Assist in the ... Bachelor's of Science in Civil Engineering * Master's degree in with an emphasis in Hydrology and ...

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Showing results 1-20

Geospatial Data Science information

See Arizona salary details

$20.5K

$72.2K

$113.7K

How much do geospatial data science jobs pay per year?

As of Jun 9, 2026, the average yearly pay for geospatial data science in Arizona is $72,216.00, according to ZipRecruiter salary data. Most workers in this role earn between $50,800.00 and $74,600.00 per year, depending on experience, location, and employer.

How does a Geospatial Data Scientist typically collaborate with other departments or teams within an organization?

Geospatial Data Scientists often work closely with professionals from diverse departments such as urban planning, environmental science, IT, and business analytics. Collaboration usually involves sharing spatial insights, integrating geospatial data with other datasets, and contributing to interdisciplinary projects that require spatial analysis or mapping. Effective communication is crucial, as you'll translate complex geospatial findings into actionable recommendations for non-technical stakeholders. This cross-functional teamwork not only broadens your understanding of organizational goals but also enhances the impact and visibility of geospatial analyses.

What is the difference between Geospatial Data Science vs GIS Analyst?

AspectGeospatial Data ScienceGIS Analyst
Required CredentialsDegree in Data Science, Geography, or related; often includes programming skillsDegree in Geography, GIS, or related; GIS certifications common
Work EnvironmentData analysis, modeling, programming, often in tech or research settingsMapping, spatial data management, using GIS software in various industries
Employer & Industry UsageTech companies, research institutions, government agencies focusing on spatial data analysisUrban planning, environmental agencies, utilities, and government agencies

While both roles work with spatial data, Geospatial Data Science emphasizes data analysis, modeling, and programming skills to extract insights from geospatial data. GIS Analysts focus more on mapping, data management, and using GIS software for spatial analysis. The roles often overlap but differ mainly in technical focus and application areas.

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

To thrive as a Geospatial Data Scientist, you need a solid background in statistics, spatial analysis, and programming, typically supported by a degree in geography, computer science, or a related field. Proficiency with GIS software (such as ArcGIS or QGIS), spatial databases, and coding languages like Python or R is essential, and certifications in GIS can be advantageous. Strong problem-solving skills, attention to detail, and effective communication help translate complex spatial data into actionable insights for diverse stakeholders. These skills ensure accurate data analysis, innovative solutions, and impactful decision-making in fields reliant on geographic information.

What is geospatial data science?

Geospatial data science is an interdisciplinary field that focuses on analyzing and interpreting data that has a geographic or spatial component. It combines techniques from data science, statistics, and geographic information systems (GIS) to extract insights, identify patterns, and solve problems related to location-based data. Professionals in this field work with mapping, remote sensing, spatial analysis, and visualization tools to support decision-making in areas like urban planning, environmental monitoring, and logistics.
What are the most commonly searched types of Geospatial Data Science jobs in Arizona? The most popular types of Geospatial Data Science jobs in Arizona are:
What are popular job titles related to Geospatial Data Science jobs in Arizona? For Geospatial Data Science jobs in Arizona, the most frequently searched job titles are:
Infographic showing various Geospatial Data Science job openings in Arizona as of May 2026, with employment types broken down into 32% Full Time, 55% Part Time, 11% Contract, and 2% Nights. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $72,216 per year, or $34.7 per hour.
Machine Learning Engineer II, Logistics AI

Machine Learning Engineer II, Logistics AI

Instacart

Glendale, AZ

Full-time

Posted 17 days ago


Instacart rating

6.7

Company rating: 6.7 out of 10

Based on 29 frontline employees who took The Breakroom Quiz


Job description

We're transforming the grocery industry

At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers.

Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table.

Instacart is a Flex First team

There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work.

About the Role:

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart's marketplace systems. You will use machine learning to devise and refine solutions in crucial areas such as routing optimization, pricing, dispatch, and mapping. You will actively contribute to initiatives, assisting in all stages from the initial concept, through prototyping and experimentation, to final implementation.

About the Team:

The Logistics AI group is responsible for the intelligence and execution behind Instacart’s fulfillment system. The team optimizes a multi-sided marketplace to ensure customers get their orders on-time and in high quality, shoppers get efficient and fulfilling work, and retailers and consumer brands get reasonable business. The team tackles hard problems in a variety of spaces, such as matching, pricing, and geospatial, as well as foundational problems executing on a high throughput system with dynamic data.

About the Job:

  • Design, develop, and deploy machine learning solutions to tackle practical challenges in the marketplace.
  • Collaborate closely with product managers, data scientists, and backend engineers to deeply understand business needs and create impactful ML/AI applications.
  • Actively engage with diverse stakeholders to ensure that solutions are well-integrated and aligned with business goals.
  • Push the envelope on our operational efficiency by continually refining and advancing our algorithms and models.

About You:

Minimum Qualifications:

  • Have a graduate degree (masters or PhD) in artificial intelligence, machine learning, operations research or equivalent self study and experience 
  • Have strong programming skills in Python and fluency in data manipulation (SQL, Pandas) and Machine Learning (scikit-learn, XGBoost, Keras/Tensorflow) tools
  • Have strong analytical skills and problem-solving ability
  • Are a strong communicator who can collaborate with diverse stakeholders across all levels

Preferred Qualifications:

  • Have 1-2 years of industry experience using machine learning to solve real-world problems with large datasets
  • Knowledge of deep learning frameworks and methodologies
  • Experience in applying machine learning and optimization techniques to solve marketplace problems

Instacart provides highly market-competitive compensation and benefits in each location where our employees work. This role is remote and the base pay range for a successful candidate is dependent on their permanent work location. Please review our Flex First remote work policy here.

Offers may vary based on many factors, such as candidate experience and skills required for the role. Additionally, this role is eligible for a new hire equity grant as well as annual refresh grants. Please read more about our benefits offerings here.

For US based candidates, the base pay ranges for a successful candidate are listed below.


What Instacart employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Instacart logo

About Instacart

Sourced by ZipRecruiter

Instacart, based in San Francisco, CA, US, operates within the retail industry, specifically grocery delivery and pick-up service. It is recognized as a pioneer in this field, delivering fresh groceries from local stores directly to customers' doors. The company, which launched its services in 2012, continues to pioneer change in the online grocery shopping sector through its commitment to cutting-edge technology, new business ideas, and dedicated service.

Industry

Technology, communication and media

Company size

10,000+ Employees

Headquarters location

San Francisco, CA, US

Year founded

2012