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Data Science Assistant Jobs in Arizona (NOW HIRING)

TSMC

Senior Data Engineer / Data Curator

Phoenix, AZ · On-site

$130K - $177K/yr

Bachelor's degree in Computer Science, Data Science, or a related field. Technical Skills: * 5+ ... Additionally, TSMC provides income-protection programs to financially assist you should you ...

TSMC

Senior Data Engineer / Data Curator

Phoenix, AZ · On-site

$130K - $177K/yr

Bachelor's degree in Computer Science, Data Science, or a related field. Technical Skills: * 5+ ... Additionally, TSMC provides income-protection programs to financially assist you should you ...

TERRACON

Assistant Scientist

Tempe, AZ

Bachelor's degree in Environmental Science or related science field. Or, in lieu of a degree, a ... Tabulate and prepare data for written reports. * May assist with report preparation by summarizing ...

TERRACON

Assistant Scientist

Tempe, AZ · On-site

Tabulate and prepare data for written reports. * May assist with report preparation by summarizing ... Bachelor's degree in Environmental Science or related science field. Or, in lieu of a degree, a ...

CommonSpirit Health

Research Scientist I

Phoenix, AZ

Your ability to plan research, contribute to publications, and assist in securing funding will be paramount. The Barrow Neuro Analytics Center (BNAC) is a data science-focused research facility led ...

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Data Science Assistant information

What are Data Science Assistants?

Data Science Assistants are professionals who support data scientists and analytics teams by handling tasks such as data collection, data cleaning, preparing datasets, conducting preliminary analyses, and creating visualizations. They often work with large datasets, assist in maintaining data integrity, and help automate routine processes. Their role allows data scientists to focus on more complex modeling and analytical work, making the overall workflow more efficient. Data Science Assistants typically have a foundational understanding of statistics, programming (such as Python or R), and data management tools.

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

To thrive as a Data Science Assistant, you need a solid understanding of statistics, data analysis, and programming (often with a background in mathematics, computer science, or a related field). Familiarity with tools like Python or R, data visualization software, and experience with databases or spreadsheet systems are typically required. Attention to detail, strong problem-solving abilities, and effective communication set outstanding candidates apart. These skills are crucial for supporting data-driven decision-making and ensuring accurate, actionable insights for organizations.

Is 40 too late for data science?

Data Science Assistants and other data science roles do not have strict age limits; many professionals start or transition into data science later in life. Success depends on acquiring relevant skills such as programming, statistics, and machine learning, which can be learned at any age through online courses, certifications, and practical experience.

How does a Data Science Assistant typically collaborate with data scientists and other team members on projects?

As a Data Science Assistant, you will frequently support data scientists by preparing datasets, conducting preliminary data analysis, and creating visualizations. You will often work closely with analysts, engineers, and subject matter experts to gather requirements and ensure data is cleaned and formatted appropriately. Collaboration is a key part of the role, as you may participate in team meetings, share findings, and help with documentation to keep projects running smoothly. This supportive environment provides an excellent opportunity to learn from experienced professionals and gain exposure to the full data science workflow.

What is the 80 20 rule in data science?

In data science, the 80/20 rule, also known as the Pareto principle, suggests that roughly 80% of the results come from 20% of the efforts or data. Data scientists often use this concept to focus on the most impactful features, data subsets, or tasks to improve model performance efficiently.

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

AspectData Science AssistantData Analyst
Required CredentialsBachelor's in Data Science, Statistics, or related fieldBachelor's in Statistics, Mathematics, or related field
Work EnvironmentTech companies, research labs, data-driven departmentsBusiness, finance, marketing, healthcare sectors
Employer & Industry UsageUsed in data science teams for supporting models and analysisUsed across industries for interpreting data and generating reports

While both roles involve working with data, a Data Science Assistant typically supports data science projects, focusing on data preparation and model testing. A Data Analyst primarily interprets data to generate insights and reports. The roles overlap in skills and work environments but differ in their core responsibilities and focus areas.

What do data assistants do?

Data Science Assistants support data analysis by collecting, cleaning, and organizing data sets. They often use tools like Excel, SQL, or Python to prepare data for modeling and reporting, assisting data scientists and analysts in project workflows.

Can I get a data scientist job with no experience?

Entry-level data science assistant roles often do not require prior experience, but candidates typically need a strong foundation in programming (such as Python or R), statistics, and data analysis. Gaining relevant skills through online courses, certifications, or personal projects can improve chances of securing such positions.
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 Assistant jobs in Arizona? For Data Science Assistant jobs in Arizona, the most frequently searched job titles are:
What job categories do people searching Data Science Assistant jobs in Arizona look for? The top searched job categories for Data Science Assistant jobs in Arizona are:
Data Science Assistant jobs near you
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 29 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

345th of 555 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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