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Data Science Jobs in Arizona (NOW HIRING)

onsemi

Sr. Manager AI & Data Science

Scottsdale, AZ

Sr. Manager AI & Data Science We are seeking a visionary and technically strong Senior Manager of AI & Data Science to lead a high-performing team focused on delivering scalable AI/ML solutions ...

Oscar Health

Data Scientist II

Tempe, AZ · Hybrid

$131K - $172K/yr

Collaborate closely with data science peers and cross-functional partners across business units * Help ensure data science processes and outputs align with broader team strategies and roadmaps

Republic Services

Data Scientist III

Phoenix, AZ · On-site

They apply analytical and data science methods to real world datasets to solve ongoing business problems. The Data Scientist III effectively communicates both technical and analytical concepts across ...

Deloitte

Manager - Data Science / Data Lake

Tempe, AZ · On-site

Experience supporting the design, development, or deployment of enterprise data science or ... artificial intelligence solutions * Experience applying artificial intelligence, machine learning ...

Republic Services

Data Scientist III

Phoenix, AZ

They apply analytical and data science methods to real world datasets to solve ongoing business problems. The Data Scientist III effectively communicates both technical and analytical concepts across ...

Republic Services

Data Scientist III

Phoenix, AZ

They apply analytical and data science methods to real world datasets to solve ongoing business problems. The Data Scientist III effectively communicates both technical and analytical concepts across ...

Oscar Health

Data Scientist II

Tempe, AZ · On-site

$131K - $172K/yr

Collaborate closely with data science peers and cross-functional partners across business units * Help ensure data science processes and outputs align with broader team strategies and roadmaps

Oscar Health

Data Scientist II

Tempe, AZ · Hybrid

$131K - $172K/yr

Collaborate closely with data science peers and cross-functional partners across business units * Help ensure data science processes and outputs align with broader team strategies and roadmaps

State Farm

Lead Data Scientist - Gen AI

Tempe, AZ

Data Science at State Farm: As a Data Scientist at State Farm, you will serve as a subject matter expert and consultant. In this role, you will share your knowledge and work to increase the use of ...

Ultra Clean Technology

Data Scientist

Phoenix, AZ · On-site

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 ...

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All JobsData Science JobsData Science Jobs in Arizona

Data Science information

See Arizona salary details

$34.9K

$114.4K

$183.1K

How much do data science jobs pay per year?

As of Jul 13, 2026, the average yearly pay for 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 data science a good career?

Data science is a growing field with high demand for professionals skilled in statistics, programming, and data analysis tools like Python and R. It offers competitive salaries, diverse industry applications, and opportunities for advancement, making it a strong career choice for those with relevant skills and education.

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

To thrive as a Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, usually supported by a degree in a quantitative field. Familiarity with machine learning libraries (like scikit-learn or TensorFlow), big data tools (such as Hadoop or Spark), and data visualization platforms is typically required. Critical thinking, problem-solving, and effective communication are vital soft skills for translating complex data insights into actionable business strategies. These skills and qualities are essential for extracting value from data, driving informed decisions, and effectively collaborating with multidisciplinary teams.

Is 40 too late for data science?

Data science is a field open to individuals of all ages, and many professionals transition into it later in their careers. Success often depends on acquiring relevant skills such as programming, statistics, and machine learning, which can be learned through online courses, bootcamps, or degrees regardless of age.

What are some common challenges faced by data scientists when working with real-world datasets?

Data scientists often encounter challenges such as missing or inconsistent data, unstructured formats, and noisy information in real-world datasets. Cleaning and preprocessing data to ensure its quality can be time-consuming but is critical for building accurate models. Additionally, data scientists may work closely with domain experts and other team members to better understand the data's context and ensure their analyses align with business objectives. Overcoming these challenges requires strong problem-solving skills and effective collaboration within cross-functional teams.

What is data science?

Data science is an interdisciplinary field that uses scientific methods, algorithms, and systems to extract insights and knowledge from structured and unstructured data. It combines skills from statistics, computer science, and domain expertise to analyze and interpret complex data sets. Data scientists work with large amounts of data to identify patterns, make predictions, and help organizations make data-driven decisions.

What jobs can a Data Scientist do?

A Data Scientist can work in roles such as data analyst, machine learning engineer, data engineer, or business intelligence analyst. These roles involve analyzing large datasets, developing predictive models, and using tools like Python, R, and SQL to support decision-making across various industries.

What is the difference between Data Science vs Data Analyst?

AspectData ScienceData Analyst
Required skillsStatistics, programming (Python, R), machine learningData visualization, SQL, basic statistics
Work environmentDeveloping models, predictive analytics, researchReporting, data cleaning, descriptive analysis
Tools usedPython, R, Jupyter, TensorFlowExcel, SQL, Tableau, Power BI
Industry usageTech, finance, healthcare, e-commerceRetail, marketing, finance, healthcare

Data Science and Data Analyst roles often overlap but differ mainly in scope. Data Scientists focus on building predictive models and advanced analytics, requiring programming and machine learning skills. Data Analysts primarily handle data cleaning, reporting, and visualization. Both roles are essential in data-driven industries, but Data Science is more technical and research-oriented, while Data Analysis emphasizes interpreting data for business insights.

What work do you do as a Data Scientist?

A Data Scientist analyzes large datasets to extract insights, build predictive models, and inform business decisions. They use programming languages like Python or R, and tools such as SQL and machine learning frameworks, often working in collaborative environments with data engineers and analysts.

What Does a Data Scientist Do?

As a Data Scientist, you are qualified to work in such diverse fields as research and development, politics, advertising and marketing, technology, healthcare, government, and higher education as well as multiple others. In general, your duties and responsibilities will be to compile and analyze relevant statistics and turn those numbers into algorithms that reveal insights that can be used by other researchers in their areas of study. Data Science can reveal things like consumer buying habits or the likelihood of success for a course of action. Other duties might vary, depending on your unique field of specialty. Related areas in which a Data Scientist might wish to focus include work as a Data Analyst, Machine Learning Engineer, and Project Manager.
More about Data Science jobs
What are the most commonly searched types of Data Science jobs in Arizona? The most popular types of Data Science jobs in Arizona are:
What are popular job titles related to Data Science jobs in Arizona? For Data Science jobs in Arizona, the most frequently searched job titles are:
What job categories do people searching Data Science jobs in Arizona look for? The top searched job categories for Data Science jobs in Arizona are:
What cities in Arizona are hiring for Data Science jobs? Cities in Arizona with the most Data Science job openings:
Data Science jobs near you
Infographic showing various 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.
Sr. Manager AI & Data Science

Sr. Manager AI & Data Science

onsemi

Scottsdale, AZ

Full-time

Re-posted 25 days ago

Onsemi rating

8.3

Company rating: 8.3 out of 10

Based on 19 frontline employees who took The Breakroom Quiz

Job description

Sr. Manager AI & Data Science

We are seeking a visionary and technically strong Senior Manager of AI & Data Science to lead a high-performing team focused on delivering scalable AI/ML solutions across onsemi's global operations. This role will be responsible for building and scaling the core AI and ML platforms, managing cross-functional initiatives, and ensuring responsible AI governance in alignment with onsemi's policies. You will report to the Sr. Director of AI & Automation and collaborate to execute on the vision to accelerate AI/ML adoption to deliver business value.

We're looking for a hands-on leader who thrives at the intersection of strategy and execution. As a player-coach, you'll be deeply involved in the technical details-guiding architectural decisions, ensuring AI safety, and shaping workflows using tools like LangGraph, Azure Machine Learning, Databricks, and MLflow. Your expertise in transformer-based models, retrieval-augmented generation (RAG), and vector databases will be instrumental in driving innovation.

But your true impact will come from leadership. You'll foster a high-performance culture rooted in technical excellence, accountability, and clarity. By mentoring a team of data scientists and machine learning engineers, you'll help turn ambitious AI roadmaps into scalable, production-ready solutions that power onsemi's digital transformation.

onsemi (Nasdaq: ON) is driving disruptive innovations to help build a better future. With a focus on automotive and industrial end-markets, the company is accelerating change in megatrends such as vehicle electrification and safety, sustainable energy grids, industrial automation, and 5G and cloud infrastructure. With a highly differentiated and innovative product portfolio, onsemi creates intelligent power and sensing technologies that solve the world's most complex challenges and leads the way in creating a safer, cleaner, and smarter world.

More details about our company benefits can be found here:

https://www.onsemi.com/careers/career-benefits

We are committed to sourcing, attracting, and hiring high-performance innovators, while providing all candidates a positive recruitment experience that builds our brand as a great place to work.


onsemi is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, ethnicity, color, religion, ancestry, national origin, age, marital status, pregnancy, sex, sexual orientation, physical or mental disability, medical condition, genetic information, military or veteran status, gender identity, gender expression, or any other protected category under applicable federal, state, or local laws.

If you are an individual with a disability and require a reasonable accommodation to complete any part of the application process, or are limited in the ability or unable to access or use this online application process and need an alternative method for applying, you may contact Talent.acquisition@onsemi.com for assistance.

Requirements: 

  • Master's or PhD in Computer Science, Data Science, Statistics, or a related field.
  • 10-15 years of experience in AI/data science, with at least 5 years in a leadership role.
  • Proven experience deploying AI/ML solutions in production environments.
  • Strong knowledge of cloud platforms (Azure preferred), MLOps, and data governance.
  • Excellent communication and stakeholder management skills.
  • Experience in semiconductor, manufacturing, or industrial domains is a plus.

Preferred Knowledge and Experience:

  • Semiconductor industry experience.
  • Experience with tools like Databricks, Azure ML, and Snowflake.
  • Understanding of ERP platform and experience in enabling AI in business functions like sales, HR, finance, operations, etc.
  • Understanding of AI security and compliance frameworks.

Competencies:

  • Self-motivated, able to multitask, prioritize, and manage time efficiently
  • Strong problem-solving skills
  • Data analysis skills. Ability to analyze complex data and turn it into actionable information
  • Collaboration and teamwork across multiple functions and stakeholders around the globe
  • Flexibility and adaptability
  • Process management / process improvement
  • Drive for results, Able to work under pressure and meet deadlines
  1. Provide Technical Leadership: Steer the team through critical architectural decisions spanning the full AI/ML stack-from foundational infrastructure like model registries, CI/CD pipelines, and feature stores, to advanced orchestration and observability frameworks for LLMs using tools such as LangGraph, MLflow, Azure ML, and Databricks.
  2. Collaborate with business domain managers to define product requirements and identify AI opportunities.
  3. Oversee data science project lifecycles, from ideation to production, ensuring alignment with business goals and technical feasibility.
  4. Ensure compliance with onsemi's Responsible AI Use and Governance Policies, including data privacy, model transparency, and ethical use.
  5. Partner with IT, data engineering, and business teams to ensure end to end project delivery & execution.
  6. Mentor and grow a team of AI, data scientists and machine learning engineers.
  7. Represent the AI function in executive forums and cross-functional steering committees.

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