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Data Analytics Masters Jobs in Arizona (NOW HIRING)

By leveraging proprietary data and analytics, our solutions are tailored for each step of our ... / MBA with 2+ years of experience * MBA or Bachelor's Degree in Engineering, Scientific field ...

Sr. Data Analyst

Tempe, AZ · On-site +1

$115K - $145K/yr

By leveraging proprietary data and analytics, our solutions are tailored for each step of our ... / MBA with 2+ years of experience * MBA or Bachelor's Degree in Engineering, Scientific field ...

Sr. Data Analyst

Tempe, AZ · On-site

$115K - $145K/yr

By leveraging proprietary data and analytics, our solutions are tailored for each step of our ... / MBA with 2+ years of experience * MBA or Bachelor's Degree in Engineering, Scientific field ...

Big Data Architect

Phoenix, AZ · On-site

$63.25 - $81.50/hr

BI & data analytics: reporting, OLAP, dashboards and predictive analytics solutions and platforms. * Masters Degree Required Additional Information Work with blueStone recruiting to find your next ...

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Showing results 1-20

Data Analytics Masters information

See Arizona salary details

$22.8K

$99.4K

$177.7K

How much do data analytics masters jobs pay per year?

As of Sep 12, 2026, the average yearly pay for data analytics masters in Arizona is $99,382.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,621.00 and $129,612.00 per year, depending on experience, location, and employer.

What is a data analytics master?

A Data Analytics Masters job typically involves analyzing large datasets to extract insights that help businesses make data-driven decisions. Professionals in this role use statistics, machine learning, and data visualization tools to interpret trends and patterns. They commonly work in industries like finance, healthcare, marketing, and technology. Strong analytical skills, programming knowledge (e.g., Python, SQL, R), and expertise in data visualization tools (e.g., Tableau, Power BI) are essential.

What is a data analytics master's degree?

A Data Analytics Masters degree is a graduate-level program that focuses on teaching students advanced skills in analyzing, interpreting, and visualizing data to help organizations make data-driven decisions. The program typically covers topics such as statistics, machine learning, data mining, data visualization, and programming languages like Python or R. Graduates are prepared for careers in data science, business analytics, and related fields, where they can apply analytical techniques to solve real-world problems. This degree is ideal for individuals who want to deepen their understanding of data and pursue specialized roles in analytics.

What are the key skills and qualifications needed to thrive as a data analytics master?

To thrive as a Data Analytics professional with a master's degree, you need strong analytical skills, expertise in statistics, and advanced knowledge of data modeling, typically supported by a relevant STEM degree. Proficiency with tools such as SQL, Python, R, Tableau, and familiarity with machine learning platforms is commonly required, along with certifications like Google Data Analytics or Microsoft Certified: Data Analyst Associate. Excellent problem-solving abilities, critical thinking, and effective communication skills help translate complex data findings into actionable business insights. These skills and qualifications are essential for transforming raw data into strategic decisions that drive organizational success.

What types of real-world projects or collaboration opportunities can a data analytics master expect during their studies?

Data Analytics Masters programs often include hands-on projects where students work with real datasets from industry partners or simulate actual business scenarios. These projects typically involve teamwork, allowing students to collaborate with peers and sometimes with professionals from related fields such as business, engineering, or IT. This collaborative environment helps students develop both technical and communication skills, and provides valuable exposure to industry-standard tools and workflows. Additionally, these experiences can lead to networking opportunities and open doors for internships or job placements upon graduation.

What is the difference between Data Analytics Masters vs Data Analyst?

AspectData Analytics MastersData Analyst
CredentialsTypically requires a master's degree in data science, analytics, or related fieldUsually requires a bachelor's degree in a related field; certifications can enhance prospects
Work EnvironmentAcademic, research, or advanced industry roles; often involves project-based workBusiness environments, working with data to generate reports and insights
Industry UsageUsed in academia, research institutions, and advanced analytics roles in industryCommon across industries like finance, healthcare, marketing, and technology

In summary, a Data Analytics Masters is an advanced qualification often required for specialized or research roles, while a Data Analyst is a more entry-level or mid-level position focused on analyzing data to support business decisions. Both roles share overlapping skills but differ in educational requirements and scope of work.

Is a master's in data analytics worth it?

A master's in data analytics can enhance job prospects for data analysts and related roles by providing advanced skills in statistical analysis, programming, and data visualization tools. It often leads to higher salaries and more senior positions, but the value depends on individual career goals and industry demand.

What can I do with a master's in data analytics?

A master's in data analytics prepares individuals for roles such as data analyst, data scientist, business intelligence analyst, or data engineer. These roles involve analyzing large datasets, creating reports, and using tools like SQL, Python, or R to support decision-making across various industries.

What are popular job titles related to Data Analytics Masters jobs in Arizona?

For Data Analytics Masters jobs in Arizona, the most frequently searched job titles are:

Infographic showing various Data Analytics Masters job openings in Arizona as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 82% Full Time, 12% Part Time, 1% Temporary, and 3% Contract. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution, with an average salary of $99,382 per year, or $47.8 per hour.

Campus Graduate Masters Summer Internship Program - 2027 Data Analytics, Enterprise Technology Servi

Phoenix, AZ • On-site

$24.05/hr

Full-time

Posted 11 days ago


American Express rating

8.6

Company rating: 8.6 out of 10

Based on 37 frontline employees who took The Breakroom Quiz


Job description


Business Unit / Role Specific Info
The Enterprise Technology Services organization partners with every part of the American Express business to power the company's growth and innovation with trust and efficiency, and drive competitive differentiation with speed. We support the delivery and operations of technology, digital, and data capabilities, platforms, and services globally. Specifically, our team is responsible for the company's technology engineering, architecture, and infrastructure, providing 24x7 support to ensure an uninterrupted, high-quality experience for customers and colleagues. We also provide product management for core enterprise platforms, and lead technology risk and information security, enterprise data governance and platforms, digital product and design, and enterprise AI platforms on behalf of the company.
At American Express, we empower early career data and analytics interns to learn, innovate, and make an impact from day one. As an Analyst Data Analytics intern in Enterprise Technology Services, you will support analytics work that helps technology teams understand portfolio performance, delivery progress, financial trends, resource utilization, and operational outcomes.
This role sits at the intersection of technology, finance, portfolio management, reporting, and data analytics. You may gather and validate data, build reports, analyze financial or delivery metrics, support dashboards, develop insights, and prepare clear recommendations that help leaders and teams make informed technology decisions.
Responsibilities
Responsibilities and What Type of Work to Expect
  • Collect, clean, validate, and organize data from portfolio, project, financial, operational, and technology delivery sources to support analysis and reporting.
  • Analyze portfolio performance, budget, forecast, resource, delivery, schedule, quality, and risk information to identify trends, insights, and areas for follow up.
  • Create and maintain dashboards, reports, key performance indicators, recurring analytics outputs, and leadership ready summaries for technology stakeholders.
  • Develop financial models, cost views, forecast summaries, scenario analyses, and variance insights that support technology portfolio and project decision making.
  • Partner with technology, finance, product, project, and business teams to understand reporting needs and translate them into accurate analytical outputs.
  • Support Software Development Lifecycle and Agile delivery reporting by analyzing delivery metrics, progress data, dependencies, and execution patterns.
  • Prepare presentations, narratives, and stakeholder updates that communicate data backed insights to technical and non technical audiences.
  • Use Agentic AI, reporting, data analytics, and productivity tools to support research, summarization, analysis, workflow efficiency, and human validated outputs.

Qualifications
Minimum Qualifications
  • Must have earned a Master's degree in Business Administration, Finance, Information Technology, Information Systems, Business Analytics, Data Analytics, Computer Science, Economics, or another relevant field before the full time start date.
  • Interest or experience in data analytics, financial management, portfolio reporting, technology delivery, business intelligence, or data informed decision making.
  • Foundational knowledge of data analytics concepts, including data collection, validation, analysis, visualization, and insight generation.
  • Foundational understanding of financial management principles such as budgeting, forecasting, cost tracking, variance analysis, or financial modeling.
  • Awareness of Software Development Lifecycle and Agile methodology concepts within a technology delivery environment.
  • Foundational understanding of Generative AI concepts, responsible use, appropriate use contexts, prompt based workflows, and human validation of AI generated outputs.
  • Strong analytical thinking, attention to detail, communication, organization, problem solving, and collaboration skills.

Preferred Qualifications
  • Master's degree candidates with an expected graduation date between December 2027 and June 2028.
  • Coursework, projects, internships, student organizations, or extracurricular experience related to data analytics, finance, business analysis, reporting, portfolio management, or technology delivery.
  • Experience using analytical, reporting, or presentation tools such as Excel, PowerPoint, SQL, Python, Tableau, Power BI, or similar platforms.
  • Exposure to financial modeling, dashboard development, key performance indicator reporting, forecast reconciliation, cost analysis, or operational analytics.
  • Interest in technology portfolio management, project performance reporting, resource planning, process improvement, or business intelligence modernization.
  • Familiarity with project or portfolio tools such as Jira, Rally, Confluence, SharePoint, Microsoft Project, or related workflow platforms.
  • Coursework, projects, research, or internship exposure to data requirements, source-to-target mapping, data quality and controls, metadata, lineage, or data governance.
  • Exposure to financial modeling, dashboard development, statistical analysis, scenario analysis, model documentation, data quality review, metadata, or data lineage concepts.
  • Interest in AI governance, model risk management, responsible AI, explainability, enterprise data architecture, predictive analytics, or quantum computing research.
  • Curiosity about Agentic AI reporting, AI enabled analytics, productivity tools, automated insight generation, and responsible validation of AI generated recommendations.
  • Ability to build clear narratives from data, communicate findings clearly, and work effectively across finance, technology, architecture, risk, product, and business teams.

Our team reviews applications on a rolling basis. We appreciate your patience while we consider your application and will contact qualified candidates regarding next steps.
Employment eligibility to work with American Express in the United States is required as the company will not pursue visa sponsorship for these positions.
Ideal Candidate Profile
We are seeking curious and analytical students who enjoy working with data, solving complex problems, and learning how analytics can support responsible technology decisions. Successful candidates will combine quantitative thinking, business curiosity, strong communication skills, and a commitment to accuracy, integrity, and continuous learning.
About Us
At American Express, our culture is built on a 175-year history of innovation, shared values and Leadership Behaviors, and an unwavering commitment to back our customers, communities, and colleagues. From delivering differentiated products to providing world-class customer service, we operate with a strong risk mindset, ensuring we continue to uphold our brand promise of trust, security, and service.
As part of Team Amex, you'll experience our powerful backing with comprehensive support for your holistic well-being and many opportunities to learn new skills, develop as a leader, and grow your career. Here, your voice and ideas matter, your work makes an impact, and together, you will help us define the future of American Express.
About the Team
We back you with benefits that support your holistic well-being so you can be and deliver your best. This means caring for you and your loved ones' physical, financial, and mental health, as well as providing the flexibility you need to thrive personally and professionally:
  • Competitive base salaries
  • Flexible work arrangements and schedules with hybrid and virtual options with Amex Flex
  • Free access to global on-site wellness centers staffed with nurses and doctors (depending on location)
  • Free and confidential counselling support through our Healthy Minds program
  • Career development and training opportunities

For a full list of Team Amex benefits, visit out Colleague Benefits Site.
American Express is an equal opportunity employer and makes employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability status, age, or any other status protected by law. American Express will consider for employment all qualified applicants, including those with arrest or conviction records, in accordance with the requirements of applicable state and local laws, including the California Fair Chance Act, the Los Angeles County Fair Chance Ordinance for Employers, and the City of Los Angeles' Fair Chance Initiative for Hiring Ordinance. For positions covered by federal and/or state banking regulations, American Express will comply with such regulations as it relates to the consideration of applicants with criminal convictions.
We back our colleagues with the support they need to thrive, professionally and personally. That's why we have Amex Flex, our enterprise working model that provides greater flexibility to colleagues while ensuring we preserve the important aspects of our unique in-person culture. Depending on role and business needs, colleagues will either work onsite, in a hybrid model (combination of in-office and virtual days) or fully virtually.
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The below represents the expected salary range for this job requisition. Ultimately, in determining your pay, we'll consider your location, experience, and other job-related factors.

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