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Data Science Fall Internship Jobs in Phoenix, AZ

State Farm

Data Scientist

Tempe, AZ · Hybrid

Our data science teams also embrace staying current with the evolving data science landscape ... Lead/mentor other Data Scientists, interns, and other technical work teams * Make strategic ...

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 ... Lead/mentor other data scientists, interns, and other technical work teams * Make strategic ...

Intel

Senior AI / Data Science Engineer

Phoenix, AZ · On-site

$105K - $143K/yr

... experience, internship experience and / or schoolwork/classes/research. The preferred ... Data Science, Machine Learning, Artificial Intelligence, Advanced Analytics. Performing yield ...

Exos

Sports Science Intern - Fall 2026

Phoenix, AZ · On-site

$15 - $19.75/hr

Job Summary: The Performance Coach Sports Science Internship is a hybrid, immersive program ... Passionate about athlete development and data-driven performance. Internship Logistics: If selected ...

Exos

Sports Science Intern - Fall 2026

Phoenix, AZ

$15 - $19.75/hr

Job Summary: The Performance Coach Sports Science Internship is a hybrid, immersive program ... Passionate about athlete development and data-driven performance. Internship Logistics: If selected ...

ASM

Simulation and Modeling Intern (Spring 2027)

Phoenix, AZ · On-site

$16.75 - $21.50/hr

About the Internship Our Fall internship provides a hands-on experience in the fast-paced and ... Familiarity with DOE, data analysis, and scripting (Python, MATLAB, or similar) * Exposure to or ...

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Data Science Fall Internship information

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How much do data science fall internship jobs pay per hour?

As of Aug 17, 2026, the average hourly pay for data science fall internship in Phoenix, AZ is $22.34, according to ZipRecruiter salary data. Most workers in this role earn between $17.16 and $24.33 per hour, depending on experience, location, and employer.

What is a data science fall internship?

A Data Science Fall Internship is a temporary, structured work experience offered by organizations during the fall semester, designed for students or recent graduates interested in data science. Interns typically work on real-world projects involving data collection, analysis, machine learning, and visualization under the guidance of experienced data scientists. This internship provides hands-on experience, exposure to industry tools and techniques, and helps participants build valuable skills for future careers in data science. It also offers networking opportunities and a chance to explore potential career paths within the field.

What types of projects can I expect to work on during a data science fall internship?

As a Data Science Fall Intern, you can expect to work on projects involving data cleaning, exploratory data analysis, and the development of predictive models using real-world datasets. Interns often collaborate with full-time data scientists and cross-functional teams to solve business problems, such as improving user engagement, optimizing processes, or generating actionable insights from large data sets. You may also participate in regular team meetings, present findings, and contribute to ongoing research or tool development. This hands-on experience helps you build both technical and communication skills within a dynamic and supportive environment.

What are the key skills and qualifications needed to thrive as a data science fall intern, and why are they important?

To thrive as a Data Science Fall Intern, you generally need a solid foundation in statistics, programming (often Python or R), and data analysis, typically supported by coursework or experience in computer science, mathematics, or related fields. Familiarity with tools like pandas, scikit-learn, SQL, and data visualization libraries, as well as version control systems like Git, is highly valued. Strong problem-solving abilities, attention to detail, and effective communication skills help interns interpret data insights and collaborate with team members. These competencies are essential for producing actionable analyses and contributing meaningfully to data-driven projects in a short-term, fast-paced internship environment.

What is the difference between Data Science Fall Internship vs Data Analyst Intern?

AspectData Science Fall InternshipData Analyst Intern
Required CredentialsEnrolled in or recent graduate of a related field (e.g., Data Science, Computer Science, Statistics)Enrolled in or recent graduate of a related field (e.g., Data Analysis, Business, Statistics)
Work EnvironmentTech companies, startups, research labs, often collaborative and project-basedBusiness firms, consulting agencies, often focused on reporting and data visualization
Employer & Industry UsageUsed by tech firms, finance, healthcare, and academia for entry-level talentCommon in corporate, marketing, and consulting sectors for supporting decision-making

The Data Science Fall Internship and Data Analyst Intern roles share similarities in required education and work environment but differ in focus. Data Science internships emphasize machine learning, programming, and statistical modeling, while Data Analyst internships focus more on data visualization, reporting, and business insights. Both are valuable entry points into data careers, often overlapping in skills but serving different industry needs.

What are popular job titles related to Data Science Fall Internship jobs in Phoenix, AZ?

For Data Science Fall Internship jobs in Phoenix, AZ, the most frequently searched job titles are:

What job categories do people searching Data Science Fall Internship jobs in Phoenix, AZ look for?

The top searched job categories for Data Science Fall Internship jobs in Phoenix, AZ are:

What cities near Phoenix, AZ are hiring for Data Science Fall Internship jobs?

Cities near Phoenix, AZ with the most Data Science Fall Internship job openings:

Data Science Fall Internship jobs near you
Infographic showing various Data Science Fall Internship job openings in Phoenix, AZ as of August 2026, with employment types broken down into 7% Internship, 61% Full Time, 25% Part Time, 5% Contract, and 2% Nights. Highlights an 84% In-person, 5% Hybrid, and 11% Remote job distribution, with an average salary of $46,477 per year, or $22.3 per hour.

Student Assistant - Data Science

ASU Enterprise Partners

Scottsdale, AZ • Hybrid

$15.25 - $19.50/hr

Part-time

Re-posted 3 days ago

Job description

Student Assistant, Data Science

In the role of Student Assistant - Data Science at ASU Enterprise Partners, you will contribute to the development and deployment of data science and AI solutions that create measurable business value.These may include analyses, predictive models, AI-enabled applications, automations, and other solutions designed to create business value.You will have the opportunity to explorenew technologiesand approaches, develop practical skills through hands-on experience, and make meaningful contributions to larger data science and AI initiatives with the support of experienced team members.

Your work will focus on developing and supporting data science and AI solutions that create measurable business value. We strive to align assignments with each student's technical background and areas of interest while providing opportunities to build new skills through hands-on experience. Projects may involve activities such as developing and validating queries, evaluating AI-generated outputs, supporting predictive models and deployed solutions, improving analytical workflows, or contributing to other initiatives that advance organizational goals.

Student employees are valued members of the Applied Data Science and Analytics (ADSA) team andhave the opportunity tocontribute to meaningful initiatives while expanding the technical and professional skills that support future careers in data science, analytics, artificial intelligence, and related fields.

This positionrequiresapproximately 20 hours per week.This is a hybrid position, with an expectation that the student works approximately 12 of the 20 weekly hours on-site.

What you'll do

  • Solution Development:Contribute to the development, testing, and refinement of data science, analytics, automation, and AI solutions that support businessobjectives.

  • Analysis & Evaluation:Assist with data analysis, solution testing, validation, and evaluation activities that support the delivery of effective solutions.

  • Solution Design & Implementation:Support the design and implementation of data-driven and AI-enabled solutions that create measurable business value.

  • Deployment & Integration:Assist with deploying, integrating, testing, andmaintainingsolutions to ensure they are reliable, scalable, and effective.

  • Collaboration:Partner with members of the Applied Data Science and Analytics (ADSA) team and other stakeholders to support organizationalobjectives.

  • Technology Application:Use modern data, analytics, cloud, and AI technologies to develop, evaluate, and support solutions.

  • Continuous Improvement:Help evaluate solution performance and contribute to ongoing enhancements based on business needs, feedback, and evolving technologies.

  • Communication:Communicate progress, results, technical concepts, and recommendations clearly to team members and stakeholders.

What you'll need

  • Technical Foundation:Experiencewith Python, SQL, and other data analysis, or technical tools commonly used in data science, analytics, software development, or artificial intelligence.

  • Analytical Thinking:Ability to evaluate information, break down complex problems, and contribute to data-driven and technology-enabled solutions.

  • Problem Solving:Demonstratedcuriosity, critical thinking, and a willingness to learn new concepts, tools, and approaches.

  • Quantitative Reasoning:Comfort working with data and applying quantitative or computational methods to practical problems.

  • Technical Learning Agility:Interest in exploring and applying emerging technologies, methodologies, and tools in support of businessobjectives.

  • Communication Skills:Ability to communicate technical concepts, progress, findings, and recommendations clearly to both technical and non-technical audiences.

  • Collaboration:Willingness to work effectively as part of a team, contribute to shared goals, and engage constructively with feedback.

  • Adaptability:Ability to work across a variety of projects and responsibilities while balancing competing priorities and evolving requirements.

Relevant qualifications

  • Currently enrolled in a Bachelor's, Master's, or other graduate degree program at Arizona State University in a technical, quantitative, or analytical discipline, ora relatedfield.Must have an expected graduation date of Fall 2027 or later.

  • Has developed foundational knowledge and skills relevant to data science, analytics, software development, artificial intelligence, or related areas through coursework, projects, research, or practical experience.

Preferred education and experience

  • Completion of an internship, research project, capstone, student organization project, or other hands-on experience involving data analysis, software development, artificial intelligence, analytics, automation, or related technical work.

  • Experience contributing to the development, testing, deployment, or support of technical solutions in academic, research, extracurricular, or professional settings.

Preferred skills and abilities

  • Technical Experience:Exposure toprogramming, data analysis, cloud technologies, artificial intelligence, automation, or related technical disciplines through coursework, projects, research, internships, or personal initiatives.

  • Data & Analytics Experience:Familiarity with working with structured or unstructured data to support analysis, reporting, decision-making, or solution development.Exposure to Google Analytics (GA4) is a plus.

  • Artificial Intelligence Exposure:Exposure to modern artificial intelligence concepts, tools, or applications and an interest in their practical use to solve real-world problems.

  • Cloud & Technology Platforms:Familiarity with cloud-based or distributed computing environments and an understanding of how technology components can be integrated to support scalable solutions.Experience with Google Cloud Platform (GCP) andBigQueryis a plus.

  • Solution Development Mindset:Interest in designing, building, testing, and continuously improving technical solutions that create measurable value.

  • Continuous Learning:Demonstratedenthusiasm for learningnew technologies, methodologies, and approaches and applying them to evolving business challenges

Benefits

  • $30 bi-weekly cell phone reimbursement

  • Hands-on experience in a professional environment

  • Professional development plans

  • Opportunity to network with ASUEP leaders and other ASU students

  • Access to LinkedIn Learning and their 8,000+ courses

  • Professional skills workshops

About ASU Enterprise Partners

ASU Enterprise Partners is a nonprofit organization whose mission is to provide an ecosystem of services to create solutions and generate resources to extend Arizona State University's reach and advance its charter. ASU Enterprise Partners supports ASU and several affiliates, including the ASU Foundation for a New American University, ASU Outreach Hub, ASURE, NEWSWELL,SkysongInnovations and University Realty.

ASU Enterprise Partners is home to several Centers of Excellence whose purpose is to provide professional services to its affiliates. The Centers of Excellence include Finance, General Counsel, Investments, Public Relations and Strategic Communications, Human Resources, Facilities and Operations, Data Analytics and Insights Planning, Budgeting and Strategy, and Technology and Solutions.

At ASU Enterprise Partners

We serve

ASU and one another with integrity,trustand compassion

We engage

step up, own it, collaborate

We innovate.

continuously, fearlessly, make decisions and take risks

We care

that everyone feels respected and valued for who they are

ASU Enterprise Partners is an Equal Opportunity Employer

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