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Volunteer Astronomy Data Analysis Jobs (NOW HIRING)

aui

ngVLA Assistant Scientist

Charlottesville, VA

$85K/yr

Previous experience in radio astronomy data reduction and analysis, software development, and/or commissioning is preferred. Competency Summary * Established record of independent research.

aui

ngVLA Assistant Scientist

Charlottesville, VA

$85K/yr

Previous experience in radio astronomy data reduction and analysis, software development, and/or commissioning is preferred. Competency Summary * Established record of independent research.

CLEAResult

EV Data Analysis Lead

Columbia, MD · On-site

$107K - $161K/yr

Paid Volunteer Time: giving back to our communities is important to us * Employee Recognition ... The EV Data Analysis Lead position is open for immediate full-time employment for qualified ...

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How much do volunteer astronomy data analysis jobs pay per hour?

As of Jul 30, 2026, the average hourly pay for volunteer astronomy data analysis in the United States is $19.14, according to ZipRecruiter salary data. Most workers in this role earn between $14.42 and $20.19 per hour, depending on experience, location, and employer.
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Volunteer Astronomy Data Analysis jobs near you
Infographic showing various Volunteer Astronomy Data Analysis job openings in the United States as of July 2026, with employment types broken down into 85% Full Time, 13% Part Time, and 2% Contract. Highlights an 80% Physical, 5% Hybrid, and 15% Remote job distribution, with an average salary of $39,804 per year, or $19.1 per hour.

Undergraduate Intern - Quantitative Data & Finance (Cross-Disciplinary

Risk Analytics Company

Cambridge, MA

Full-time

Re-posted 26 days ago

Job description

Position Overview
We are seeking an undergraduate student to support our Finance and IT teams with a focus on data analysis and quantitative problem-solving. This internship provides hands-on experience working with financial datasets, basic modeling, and tools used in data-driven decision-making.
We welcome candidates from analytical and cross-disciplinary backgrounds—including mathematics, applied mathematics, statistics, economics, engineering, computer science, physics, astrophysics, quantum computing, biotech and other data-driven fields—who are interested in applying quantitative thinking to real-world business and financial problems.
Key Responsibilities
  • Work with structured datasets to support basic financial and operational analysis 
  • Assist in organizing, cleaning, and validating data for reporting and modeling 
  • Build and maintain spreadsheets and simple analytical models in Excel 
  • Support development of reports, dashboards, and visualizations 
  • Identify patterns, inconsistencies, or trends in data 
  • Assist with automation or efficiency improvements using tools like Excel, SQL, or Python (where applicable) 
  • Collaborate with team members on data, finance, and technology-related tasks 
  • Apply quantitative or analytical approaches from coursework to practical business problems 
Required Qualifications
  • Currently pursuing a Bachelor’s degree in a quantitative or analytical field (e.g., Mathematics, Applied Mathematics, Physics, Astrophysics, Statistics, Economics, Computer Science, Quantum Computing, Engineering, Finance, Biotech, or other data-driven discipline) 
  • Strong problem-solving and analytical thinking skills 
  • Familiarity with: 
    • Microsoft Excel (formulas, basic functions) 
    • Microsoft Office (Word, PowerPoint) 
  • Comfort working with numbers and structured data 
  • Strong attention to detail and willingness to learn 
Preferred Qualifications
  • Exposure to programming or data tools (Python, SQL, R, or similar) through coursework or projects 
  • Experience with Excel functions (e.g., VLOOKUP, pivot tables) 
  • Introductory knowledge of statistics, probability, or data analysis 
  • Interest in financial markets, data analytics, or fintech 
  • Coursework or projects involving: 
    • Data analysis or visualization
  • Mathematical modeling 
  • Machine learning (introductory) 
  • Computational or applied problem-solving 
What You’ll Gain
  • Hands-on experience applying quantitative skills in a real-world business environment 
  • Exposure to financial data, analytics workflows, and decision-making processes 
  • Opportunity to build foundational data and modeling skills 
  • Mentorship and professional development 
  • Insight into career paths in quantitative finance, data science, and analytics 
Internship Details
  • Summer 2026, with possible extensionÂ