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Data Science Engineer Jobs in Arizona (NOW HIRING)

Data Scientist II

Tempe, AZ · On-site

$131K - $172K/yr

... engineering, product and data stakeholders to deliver impactful solutions. This is a mid-level role ... Help ensure data science processes and outputs align with broader team strategies and roadmaps

Data Scientist II

Tempe, AZ · Hybrid

$131K - $172K/yr

... engineering, product and data stakeholders to deliver impactful solutions. This is a mid-level role ... Help ensure data science processes and outputs align with broader team strategies and roadmaps

Data Scientist

Scottsdale, AZ · On-site

$80K - $120K/yr

... Engineering and working with LLMs (Open AI, Anthropic Claude) preferred * Experience with Azure Data Factory, Azure Functions, Azure Open AI preferred * Master's degree in Data Science, CS ...

Required : • Bachelor's degree in Data Science, Computer Science, Statistics, Engineering, Mathematics, or a related field. • 3-5 years of experience in data science or advanced analytics ...

Bachelor's degree in data science, Statistics, Mathematics, Economics, Industrial-Organizational ... Proficiency in SQL and at least one analytical programming language such as Python or R.

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Showing results 1-20

Data Science Engineer information

See Arizona salary details

$41.5K

$120.9K

$165.4K

How much do data science engineer jobs pay per year?

As of Jul 16, 2026, the average yearly pay for data science engineer in Arizona is $120,881.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,700.00 and $128,100.00 per year, depending on experience, location, and employer.

What engineers make 500,000?

Senior data science engineers, machine learning engineers, and software engineers with extensive experience and advanced skills in areas like AI, big data, and cloud computing can earn salaries of $500,000 or more, especially in high-cost-of-living regions or within top tech companies. Achieving this level often requires advanced degrees, certifications, and a strong track record of impactful projects.

Is 30 too late for data science?

Data Science Engineers can enter the field at any age, including 30, as success depends on skills, experience, and continuous learning. Many professionals transition into data science later in their careers by acquiring relevant knowledge in programming, statistics, and tools like Python or R. Age is less important than demonstrated expertise and the ability to adapt to evolving technologies.

What are the key skills and qualifications needed to thrive in the Data Science Engineer position, and why are they important?

A Data Science Engineer should have a strong background in statistics, machine learning, programming (typically Python or R), and data engineering, often supported by a degree in computer science, engineering, or a related field. Familiarity with data processing frameworks (like Spark or Hadoop), cloud platforms (AWS, GCP, or Azure), and certifications in data science or cloud technology are highly valued. Excellent problem-solving skills, communication abilities, and collaboration are essential soft skills for working effectively in cross-functional teams. These competencies enable Data Science Engineers to build scalable data solutions, deliver actionable insights, and drive business impact.

What are the typical daily responsibilities of a Data Science Engineer?

Data Science Engineers typically spend their days designing and building data pipelines, preparing and cleaning large datasets, and developing machine learning models to solve business problems. They work closely with data scientists, software engineers, and business stakeholders to translate requirements into scalable technical solutions. Responsibilities also include deploying models to production, monitoring their performance, and iterating on solutions based on feedback. This role offers a dynamic mix of coding, data analysis, and teamwork, making each day varied and intellectually engaging.

What is a Data Science Engineer job?

A Data Science Engineer is a professional who bridges the gap between data science and software engineering. They focus on designing, building, and maintaining scalable data pipelines, infrastructure, and machine learning models for production use. Their role involves data preprocessing, model deployment, performance optimization, and integrating AI solutions into applications. They work closely with data scientists, software engineers, and DevOps teams to ensure efficient data workflows.

What does a data science engineer do?

A data science engineer designs, develops, and maintains data pipelines and infrastructure to support data analysis and machine learning models. They work with large datasets, use programming languages like Python or Scala, and often collaborate with data scientists and software engineers to ensure data quality and accessibility.

Is data science high paying?

Data science engineers typically earn high salaries due to their specialized skills in statistical analysis, programming, and machine learning. Salaries vary by experience, location, and industry, but data science roles are generally considered well-compensated within the tech field.
What are popular job titles related to Data Science Engineer jobs in Arizona? For Data Science Engineer jobs in Arizona, the most frequently searched job titles are:
What cities in Arizona are hiring for Data Science Engineer jobs? Cities in Arizona with the most Data Science Engineer job openings:
Infographic showing various Data Science Engineer 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 $120,881 per year, or $58.1 per hour.
Senior Data Engineer, Predictive Modeling

Senior Data Engineer, Predictive Modeling

Carvana

Tempe, AZ

$101K - $137K/yr

Other

Medical, Dental, Vision, Retirement

Re-posted 10 days ago


Carvana rating

6.9

Company rating: 6.9 out of 10

Based on 274 frontline employees who took The Breakroom Quiz

161st of 727 rated retailers


Job description

About Carvana...

At Carvana, we're changing the way people buy and sell cars. With an ambitious vision and a fundamentally different approach designed to be fun, fast, and fair, Carvana became the fastest-growing automotive retailer in history. We expanded nationally, went public on the New York Stock Exchange, sold our 1 millionth car, and reached the Fortune 500, all in just eight years.

Today, with 4 million retail customers and counting, Carvana is both the fastest-growing and the most profitable public automotive retailer, and we're just getting started. We continue to raise the bar for our customers as we tackle the enormous opportunity still ahead in the largest consumer vertical.

Working here means being part of a team that embraces change, celebrates creative problem solving, and always strives to be better. At Carvana, you'll have the opportunity to take on meaningful challenges, learn quickly, and help shape the future of automotive retail. If you're driven to grow and make an impact as part of a collaborative team, you'll fit right in. Learn more about what it's like to work here from the people that already do. 

Work Model: This is a 100% on-site role at our Tempe office, Monday through Friday.

About the team and position

In today's world, data is king and this is the team with all the data. If you're excited about understanding complex data sets from disparate sources, this is the team for you. Our data science and analytics team automates everything Carvana does from modeling consumer behavior to understanding how to make our users' lives better. 

We're not just building data pipelines; we're engineering intelligent systems that predict the future and automate complex decisions. This team takes data from across Carvana and external sources to understand past consumer behavior and predict future trends. Whether we're assessing credit risk, optimizing inventory and pricing strategies, or building AI agents that accelerate our analysts' productivity, we engineer solutions that directly impact millions of customers. As a Senior Data Engineer on this team, you'll help architect the technical foundation that makes our data science magic possible and scalable. 

What you'll be doing

  • Refactor and productionalize Python code from Data Scientists and Analysts, transforming experimental notebooks into reliable, maintainable, and production-ready applications with proper testing, error handling, and documentation.
  • Design, architect, and maintain robust, scalable predictive modeling data pipelines across our data science ecosystem.
  • Design, develop, and maintain internal tooling that accelerates productivity for our Analysts, Data Scientists, and Data Engineers.
  • Support data scientists and software engineers in building and deploying new RESTful services.
  • Apply software engineering best practices including code reviews, version control, testing frameworks, and continuous integration to ensure high-quality, maintainable codebases.
  • Design and develop high-availability applications using technologies like Docker and Kubernetes with focus on scalability, reliability, and observability.
  • Develop comprehensive solutions for application logging, error reporting, alerting, and task scheduling across distributed systems.
  • Design both relational and non-relational data models for optimal storage and retrieval, considering performance, cost, and maintainability.
  • Create robust ETL/ELT processes to integrate data between different systems and formats, ensuring data quality and lineage tracking.
  • Design processes that contain sensitive data in a responsible manner (using certificates, hashing, AD permissions), ensuring that necessary security practices are followed.
  • Read beyond initial project specifications to identify opportunities for improvement, additional functionality, and technical debt reduction.
  • Collaborate with stakeholders to translate business requirements into scalable technical solutions.
  • Mentor junior engineers and provide technical guidance on software engineering practices and data architecture decisions.
  • Stay current with emerging technologies in data engineering, AI/ML tooling, and agentic workflows that can enhance team capabilities. 
  • Excellent communication skills to explain technical concepts clearly
  • Other duties as assigned.

What you should know

  • Bachelor's degree in Computer Science, Engineering, Applied Math, or Hard Sciences, or similar field from an accredited undergraduate institution required.
  • 5+ years of experience in data engineering and data warehousing.
  • 2+ years of experience building production systems designed for scalability, availability, and robustness with emphasis on code quality and maintainability.
  • Strong software engineering fundamentals including object-oriented design, design patterns, testing methodologies, and code review practices.
  • Strong experience with at least one cloud service platform provider (AWS, GCP, Azure).
  • Strong coding and application development skills in Python.
  • Strong experience with enterprise software development using modern tools and approaches including:
    • Docker, Kubernetes, and container orchestration
    • Continuous Integration/Continuous Deployment (CI/CD) pipelines
    • Version control systems (Git) and collaborative development workflows
    • Code quality tools (linting, static analysis, dependency management)   
  • Fluency in SQL and NoSQL databases with understanding of data modeling and optimization techniques.
  • Knowledge of API design, microservices architecture, and integration patterns for connecting AI agents with backend systems.
  • Familiarity with DevOps principles and CI/CD pipelines
  • Ability to independently manage and prioritize efforts and complete projects.
  • Experience with AI/ML tooling and agentic workflow development is a strong plus.
  • Strong communication skills with ability to explain technical concepts to both technical and non-technical stakeholders.

The technical stack you'll be able to work with includes

  • Docker / Kubernetes
  • Cloud service platform providers (GCP, Azure) 
  • Python
    • Flask
    • Object-oriented Programming
    • Data Science ecosystem (numpy, scikit-learn, Jupyter)
  • Snowflake
  • SQL Server and various database technologies
  • Apache Spark, DataBricks
  • Git

What we'll offer in return

  • Full-Time Salary Position with a competitive salary.
  • Medical, Dental, and Vision benefits.
  • 401K with company match.
  • A multitude of perks including student loan payments, discounts on vehicles, benefits for your pets, and much more.
  • A great wellness program to keep you healthy and happy both physically and mentally.
  • Access to opportunities to expand your skill set and share your knowledge with others across the organization.
  • A company culture of promotions from within, with a start-up atmosphere allowing for varied and rapid career development.
  • A seat in one of the fastest-growing companies in the country.

Other requirements

To be able to do your job at Carvana, there are some basic requirements we want to share with you.

  • Must be able to read, write, speak and understand English.

Of course, we'll make any reasonable accommodations for those with disabilities to perform the essential functions of their jobs. 

Legal stuff

Hiring is contingent on passing a complete background check.  This role is eligible for visa sponsorship.

Carvana is an equal employment opportunity employer.  All applicants receive consideration for employment without regard to race, color, religion, gender, sexual orientation, gender identity or expression, marital status, national origin, age, mental or physical disability, protected veteran status, or genetic information, or any other basis protected by applicable law.  Carvana also prohibits harassment of applicants or employees based on any of these protected categories.

Please note this job description is not designed to contain a comprehensive listing of activities, duties, or responsibilities that are required of the employee for this job. Duties, responsibilities, and activities may change at any time with or without notice. 


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About Carvana

Sourced by ZipRecruiter

At Carvana, we sell cars, but we're not salespeople. Since 2013, we've been making it our mission to change the way people buy cars. We saw a huge problem with how much it can suck to buy a car the traditional way, so we committed ourselves to tackling one of the largest, yet-to-be-disrupted markets in the world - the $1T per year U.S. car market (yes, that's $Trillion with a "T").

Industry

Automobile dealers

Company size

5,001 - 10,000 Employees

Headquarters location

Tempe, AZ, US

Year founded

2011