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Trainee Data Science Jobs in Arizona (NOW HIRING)

No prior neurodiagnostic experience is required--just a strong work ethic, a scientific mindset ... Observe and support neurophysiological data collection during surgeries * Participate in structured ...

No prior neurodiagnostic experience is required-just a strong work ethic, a scientific mindset, and ... Observe and support neurophysiological data collection during surgeries * Participate in structured ...

No prior neurodiagnostic experience is required-just a strong work ethic, a scientific mindset, and ... Observe and support neurophysiological data collection during surgeries * Participate in structured ...

Through our unparalleled science, data, technology and laboratory network, we advance diagnostics ... Labcorp is seeking a Technologist Trainee join our team in Phoenix, AZ. Work Schedule: Tuesday ...

Through our unparalleled science, data, technology and laboratory network, we advance diagnostics ... Labcorp is seeking a Technologist Trainee join our team in Phoenix, AZ. Work Schedule: Tuesday ...

Through our unparalleled science, data, technology and laboratory network, we advance diagnostics ... Labcorp is seeking a Technologist Trainee join our team in Phoenix, AZ. Work Schedule: Tuesday ...

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Trainee Data Science information

See Arizona salary details

$34.9K

$114.4K

$183.1K

How much do trainee data science jobs pay per year?

As of Jul 28, 2026, the average yearly pay for trainee 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.

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

To thrive as a Trainee Data Scientist, you need a foundational understanding of statistics, programming (often Python or R), and data analysis, usually supported by a relevant degree or coursework in mathematics, computer science, or engineering. Familiarity with data visualization tools (such as Tableau or Power BI), machine learning libraries (like scikit-learn or TensorFlow), and basic database systems is often expected. Strong problem-solving skills, curiosity, and effective communication help you interpret data insights and collaborate with team members. These skills are crucial for extracting actionable insights from data and contributing meaningfully to data-driven projects.

What is the difference between Trainee Data Science vs Data Analyst?

AspectTrainee Data ScienceData Analyst
Required CredentialsBasic degree in related field, entry-level certificationsDegree in statistics, mathematics, or related field, often with certifications
Work EnvironmentInternship or entry-level role in tech or finance companiesBusiness, finance, marketing departments across industries
Employer & Industry UsageStart of data career path, training-focused rolesData-driven decision making, reporting, and analysis

In summary, a Trainee Data Science role is an entry-level position focused on learning and developing skills in data science, often as part of an internship or training program. A Data Analyst typically has more experience in analyzing data, creating reports, and supporting business decisions. Both roles are essential in data-driven industries but differ mainly in experience level and scope of responsibilities.

What does a Trainee Data Scientist do?

A Trainee Data Scientist assists in gathering, cleaning, and analyzing data to support business decisions. They work under the guidance of senior data scientists to learn about data modeling, statistical analysis, and using tools such as Python, R, or SQL. Their responsibilities often include preparing reports, visualizing data, and contributing to the development of predictive models. The goal is to build foundational skills and gain hands-on experience in the field of data science.

What are some common challenges faced by Trainee Data Scientists during their initial projects, and how can they overcome them?

Trainee Data Scientists often encounter challenges such as working with messy or incomplete datasets, understanding complex business problems, and selecting the appropriate modeling techniques. Collaborating closely with experienced team members and seeking feedback can help trainees navigate these obstacles. Additionally, actively participating in code reviews and knowledge-sharing sessions accelerates learning and builds confidence in tackling real-world data science tasks.
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 Trainee Data Science jobs in Arizona? For Trainee Data Science jobs in Arizona, the most frequently searched job titles are:
What job categories do people searching Trainee Data Science jobs in Arizona look for? The top searched job categories for Trainee Data Science jobs in Arizona are:
What cities in Arizona are hiring for Trainee Data Science jobs? Cities in Arizona with the most Trainee Data Science job openings:
Infographic showing various Trainee Data Science job openings in Arizona as of July 2026, with employment types broken down into 1% As Needed, 86% Full Time, 10% Part Time, 1% Temporary, and 2% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $114,378 per year, or $55 per hour.
Assistant, Associate or Full Professor, Biomedical Informatics (TT) (MD, PhD , MD/PhD) (Phoenix)

Assistant, Associate or Full Professor, Biomedical Informatics (TT) (MD, PhD , MD/PhD) (Phoenix)

University of Arizona

Phoenix, AZ

Other

Posted 12 days ago


University Of Arizona rating

7.2

Company rating: 7.2 out of 10

Based on 67 frontline employees who took The Breakroom Quiz

384th of 612 rated colleges and universities


Job description

  • Have demonstrated ability to design, develop and apply state-of-the-art Data Science, ML and/or AI methodologies to biomedical text data, imaging data, omics data and other relevant healthcare data.
  • Experience collaborating with biomedical research programs, clinical partners or health care systems.
  • Evidence of strong interdisciplinary communication skills and ability to work in multi-stakeholder environments.
  • Develop and sustain an independent, externally funded research program, with a strong publication record and clear trajectory toward national impact.
  • Have demonstrated experience with real-world clinical data modalities (e.g., EHR, imaging, wearables/remote monitoring, clinical text) and rigorous evaluation/validation practices supporting translation to clinical workflows, population health, and disease-specific applications.
  • Experience designing multimodal and longitudinal models (e.g., sequential prediction, multimodal fusion, graph-based learning) for diagnostic/prognostic applications.
  • Teaching service expectations:
    • Teach graduate program or undergraduate courses in biomedical informatics / data science / AI and participate in curriculum development.
    • Participate in departmental, college and professional services (committees, peer review, editorial/reviewer activities).
  • Candidatespursuing senior appointments should additionally demonstrate:
    • Have a record of successful independent program development and leadership.
    • National distinction in research, teaching or patient care, within an academic environment.
    • Evidence of mentorship of junior faculty and trainees; or has served as a joint mentor on interdisciplinary teams.

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