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Science Visualization Jobs in Arizona (NOW HIRING)

Swoon Technology Resources LLC

Scientist 2

Scottsdale, AZ · On-site

$75K - $81K/yr

Work includes data extraction, cleaning, statistical analysis, visualization, survey research ... Familiarity with learning science or VR-based education research Education / Certifications PhD ...

Peraton

Data Scientist

Fort Huachuca, AZ · On-site

As a Data Scientist, you will work collaboratively with cross-functional teams to extract, analyze ... and visualization to identify trends and patterns. • Stay up-to-date with the latest industry ...

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Science Visualization information

How does a Science Visualization professional typically collaborate with researchers and other stakeholders during a project?

Science Visualization professionals often work closely with researchers, subject matter experts, and communication teams to accurately represent complex data and scientific concepts. Early in a project, they attend meetings to understand the research goals and identify key messages. Throughout the process, they maintain open communication to ensure that visualizations are both scientifically accurate and visually engaging. This collaboration may involve iterative feedback sessions, adjustments to visual elements, and discussions about the best formats for target audiences. Such teamwork is essential for producing effective and credible visual content.

What is the difference between Science Visualization vs Scientific Illustrator?

AspectScience VisualizationScientific Illustrator
Required CredentialsDegree in science, visualization, or related fields; skills in 3D modeling and visualization softwareDegree in fine arts, illustration, or related fields; proficiency in traditional and digital illustration tools
Work EnvironmentResearch labs, universities, media companies, scientific institutionsPublishing houses, research institutions, freelance work, scientific publications
Employer & Industry UsageUsed by scientists and educators to create visual data representationsUsed by publishers, researchers, and museums to produce detailed scientific illustrations

Science Visualization focuses on creating digital visual representations of scientific data and concepts, often using 3D modeling and animation. Scientific Illustrators produce detailed, hand-drawn or digital illustrations to communicate scientific ideas visually. While both roles require scientific understanding, visualization emphasizes data-driven visuals, whereas illustration emphasizes artistic accuracy and detail.

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

To thrive as a Science Visualization Specialist, you need a solid background in scientific concepts, data analysis, and visual storytelling, often supported by a degree in science, graphic design, or a related field. Proficiency with visualization tools such as Python (Matplotlib, Seaborn), R, Adobe Creative Suite, or 3D modeling software is typically required. Strong communication, creativity, and attention to detail help translate complex data into clear, engaging visuals for diverse audiences. These skills are crucial for accurately conveying scientific information and fostering understanding among stakeholders and the public.

What is science visualization?

Science visualization is the process of creating visual representations of scientific data or concepts to make them easier to understand and communicate. This can include charts, graphs, animations, 3D models, and interactive graphics. Science visualization helps researchers, educators, and the public interpret complex information, discover patterns, and share findings effectively. It combines expertise in science, data analysis, and visual design.
What are popular job titles related to Science Visualization jobs in Arizona? For Science Visualization jobs in Arizona, the most frequently searched job titles are:
What job categories do people searching Science Visualization jobs in Arizona look for? The top searched job categories for Science Visualization jobs in Arizona are:
What cities in Arizona are hiring for Science Visualization jobs? Cities in Arizona with the most Science Visualization job openings:
Science Visualization jobs near you

Scientist 2

Swoon Technology Resources LLC

Scottsdale, AZ • On-site

$75K - $81K/yr

Full-time

Posted 20 days ago

Job description

Location: Scottsdale,Arizona
Expected Start Date: Apr 7, 2025
Salary: $75,000 - $81,500
Bring the role to life for me:
This is a highly execution-focused quantitative research role supporting established Dreamscape Learn (DSL) studies.
  • The researcher is stepping into well-structured, well-documented projects - this is not exploratory research
  • There is extensive existing documentation, surveys, datasets, and reporting templates
  • The primary responsibility is executing analysis and producing reports, not designing new studies
  • Work is fast-paced and deadline-driven (e.g., multiple high-priority reports due at the same time)
  • Success in the first 12 months looks like:
    • Consistently delivering high-quality quantitative reports
    • Synthesizing findings into clear written takeaways
    • Managing multiple concurrent studies without getting overwhelmed
  • Once they've proven strong execution, they may gradually:
    • Pitch additional analyses
    • Contribute more meaningfully to research design
This role requires someone who is:
  • Extremely organized
  • Comfortable with some ambiguity and competing priorities
  • Strong in written communication (summarizing long-term research clearly)

  • From JD:
    • This role is primarily focused on executing applied quantitative research, with some contribution to research design and methodology as needed.
    • The researcher will support scholarly and operational research for Dreamscape Learn (DSL), ASU's virtual-reality-based learning products.
    • Work includes data extraction, cleaning, statistical analysis, visualization, survey research, reporting, and stakeholder collaboration.
    • Research is action-oriented and operational, intended to inform pedagogy, engagement, learning technology decisions, and equity outcomes.

About Dreamscape Learn (DSL)
Dreamscape Learn is a collaboration between ASU and Dreamscape Immersive, founded during COVID. It combines storytelling, virtual reality, and curriculum design to improve outcomes in high-failure-rate courses.
Examples include:
  • Biology and chemistry courses where students explore concepts (e.g., going inside atoms) through VR
  • WP Carey projects where students experience a virtual Starbucks from a supply-chain perspective, observing real-world operational dynamics (e.g., peak hours, process flow)

  • Are there active Dreamscape Learn (DSL) studies this hire would step into right away, or would they be launching new research?
    • JD:
      • ongoing mixed-methods Dreamscape Learn (DSL) studies already exist, and this person will step into active research while also supporting iterative research on newly developed DSL products.

What types of quantitative analyses does the team run most often today?
  • Descriptive statistics (primary)
  • Comparisons across student cohorts (e.g., pass/fail, demographics)
  • Outcome analysis across large student populations (e.g., 1,000+ students)
  • Occasional regression analysis (not heavy or advanced modeling)

Top 3-5 responsibilities
  1. Execute quantitative analyses in R using existing datasets and frameworks
  2. Clean, transform, and manage research data efficiently
  3. Produce clear, structured reports with written key takeaways
  4. Support multiple concurrent DSL studies and reporting timelines
  5. Collaborate internally with researchers and stakeholders (internal-facing only)

Required Qualifications - What are the true must haves - what does this person need to come in already knowing?
Hard Skills
  1. Strong quantitative data analysis skills using R
  2. Data cleaning, transformation, and visualization
  3. Experience with quantitative research methodologies
  4. Survey research experience (Qualtrics preferred)
  5. Ability to manage multiple research projects and files

Nice to Have
  1. SQL experience
  2. Experience with higher education research or institutional data
  3. Familiarity with learning science or VR-based education research

Education / Certifications
PhD required
  • Discipline must have a strong statistical foundation
  • STEM-related fields are ideal (science, technology, engineering, math)
  • Candidates must have taken statistics during their PhD and actively used R

What level of R expertise is required on day one?
  • Must be able to:
    • Independently analyze data in R
    • Write and run analysis code without assistance
    • Deliver clean, repeatable outputs
  • This cannot be someone who:
    • "Knows R conceptually"
    • Relies on ChatGPT or AI to generate code
  • They do not want to train someone on R
Nice to Have
  1. SQL experience (joins, basic querying)
  2. Experience with higher education or institutional research data
  3. Familiarity with learning science or VR-based education research

Soft Skills
  1. Strong written communication (clear synthesis of long-term research findings)
  2. Ability to stay calm and organized under heavy workload
  3. Comfortable working heads-down with limited external presentation exposure

Disqualifiers - Do NOT Want to See
  1. Candidates who cannot demonstrate real, hands-on R experience
  2. "Vibe coders" or candidates dependent on AI to write analysis code
  3. Qualitative-only researchers or tools (e.g., MaxQDA, Dedoose, ATLAS.ti)

Where Are Candidates Missing the Mark?
  • Claiming R experience but unable to demonstrate it

Screening Questions to Use Up Front
  • Walk me through how you've used R in your dissertation or recent research
  • What types of statistical analyses do you run most often in R?
  • How do you manage multiple research deadlines at once?
  • Can you share an example of a report you've produced summarizing long-term findings?
Interview Process
  • Round 1 (Panel):
    • Selena (lead)
    • Kevin (Senior Researcher)
    • Bailey (slightly more senior colleague)
  • Round 2 Annie
  • Technical Assessment:
    • R-based assignment
  • Sponsorship is possible for the right candidate, but must be discussed upfront

Apply