... photometry, simulations, LaTeX, Jupyter notebooks, or scientific visualization. • Experience ... remote teams of researchers, educators, reviewers, annotators, science writers, or QAs. • ...
... photometry, simulations, LaTeX, Jupyter notebooks, or scientific visualization. • Experience ... remote teams of researchers, educators, reviewers, annotators, science writers, or QAs. • ...
Remote Photometry information
See salary details
$83.5K - $91.5K
5% of jobs
$91.5K - $99.4K
6% of jobs
$99.4K - $107.4K
12% of jobs
$108.6K is the 25th percentile. Wages below this are outliers.
$107.4K - $115.3K
12% of jobs
$115.3K - $123.3K
14% of jobs
The median wage is $124.1K / yr.
$123.3K - $131.2K
15% of jobs
$131.2K - $139.2K
11% of jobs
$140.2K is the 75th percentile. Wages above this are outliers.
$139.2K - $147.1K
11% of jobs
$147.1K - $155.1K
7% of jobs
$155.1K - $163K
4% of jobs
$163K - $171K
4% of jobs
$83.5K
$127K
$171K
How much do remote photometry jobs pay per year?
As of Jul 14, 2026, the average yearly pay for remote photometry in the United States is $127,031.00, according to ZipRecruiter salary data. Most workers in this role earn between $109,000.00 and $143,500.00 per year, depending on experience, location, and employer.
What are some common challenges faced by professionals in remote photometry, and how can they be addressed?
Professionals in remote photometry often encounter challenges such as limited access to on-site equipment, managing data quality from remote sensors, and coordinating with distributed teams. Addressing these challenges typically involves leveraging reliable remote sensing software, establishing clear communication channels with colleagues, and adhering to standardized protocols for data calibration and analysis. By staying updated on technological advancements and participating in ongoing training, remote photometry specialists can maintain accurate results and effective collaboration.
What are the key skills and qualifications needed to thrive as a Remote Photometry Specialist, and why are they important?
To thrive as a Remote Photometry Specialist, you need a solid background in physics or astronomy, strong analytical skills, and experience with photometric data analysis. Familiarity with remote sensing tools, photometry software (such as IRAF or AstroImageJ), and scripting languages like Python is typically required. Attention to detail, problem-solving ability, and effective communication are crucial soft skills for collaborating with research teams and interpreting complex data. These competencies ensure accurate data collection, efficient remote operations, and meaningful scientific insights.
What is remote photometry?
Remote photometry is the process of measuring the intensity and properties of light from a distance, often using automated or digital tools. It is commonly used in fields like astronomy, environmental science, and remote sensing to analyze light emitted or reflected by objects without direct physical contact. Remote photometrists may operate telescopes, satellites, or sensors to gather and interpret data, enabling research and monitoring in locations that are difficult or impossible to access in person.
More about Remote Photometry jobs
What cities are hiring for Remote Photometry jobs? Cities with the most Remote Photometry job openings:
What are the most commonly searched types of Photometry jobs? The most popular types of Photometry jobs are:
What states have the most Remote Photometry jobs? States with the most job openings for Remote Photometry jobs include:
What job categories do people searching Remote Photometry jobs look for? The top searched job categories for Remote Photometry jobs are:
Full-time
Posted 14 days ago
Job description
Job Summary:
YO IT Consulting is a fast-growing AI Data Services company delivering training data for many of the world’s largest AI companies and foundation-model labs. They are seeking an Astronomer Quality Assurance Lead to oversee quality and consistency in astronomy and astrophysics AI training projects, ensuring that all contributions meet the expected standards of accuracy and clarity.
Responsibilities:
• Quality monitoring: Spot-check astronomy/astrophysics items, identify quality issues, provide ongoing feedback through DMs, and escalate recurring or critical issues.
• Scientific review: Evaluate AI-generated astronomy/astrophysics explanations, calculations, diagrams, observational interpretations, comparisons, and step-by-step reasoning for accuracy and clarity.
• Trainer and QA communication: Update trainers and QAs on Discord about new item guidelines, project changes, workflow updates, quality expectations, and astronomy/astrophysics-specific review standards.
• Question handling: Respond to trainer/QA questions clearly and promptly, especially around physical assumptions, units, astronomical terminology, observational methods, formulas, and rubric interpretation.
• Trainer/QA activation management: DM contributors who are inactive or not working, encourage activation, track follow-ups, and flag availability issues when needed.
• Documentation: Create and maintain astronomy/astrophysics project documentation, including style guides, trackers, FAQs, quality notes, examples, honeypots, calibration tasks, and onboarding materials.
• Onboarding and training: Schedule and run onboarding/training calls with trainers and QAs to explain project expectations, workflows, rubrics, quality standards, and astronomy/astrophysics-specific review requirements.
• Quality alignment: Ensure all trainers and QAs apply astronomy/astrophysics review guidelines consistently and understand updates as projects evolve.
• Risk review: Flag misleading, overconfident, physically impossible, numerically incorrect, or poorly sourced astronomy/astrophysics claims.
• Process improvement: Identify recurring quality gaps, propose workflow improvements, and help build scalable QA processes for astronomy/astrophysics AI training projects.
Qualifications:
Required:
• Bachelor’s, Master’s, or PhD degree in Astronomy, Astrophysics, Physics, Space Science, Planetary Science, Cosmology, or a closely related field.
• Strong grasp of the English language to follow project guidelines, communicate with teams, and provide clear written feedback.
• 3+ years of experience in astronomy/astrophysics research, teaching, science communication, academic review, data analysis, observatory work, or related scientific workflows.
• Strong understanding of celestial mechanics, stellar evolution, galaxies, cosmology, electromagnetic radiation, observational methods, spectroscopy, planetary systems, black holes, and scientific uncertainty.
• Ability to evaluate astronomy/astrophysics content against detailed rubrics and identify issues such as incorrect physical assumptions, wrong units, flawed calculations, hallucinated facts, misleading explanations, or oversimplified conclusions.
• Comfortable working in fast-moving remote environments using tools such as Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems.
• Highly detail-oriented and organized, with the ability to maintain style guides, FAQs, trackers, onboarding materials, calibration tasks, and documentation.
Preferred:
• Familiarity with tools or methods such as Python, astronomical datasets, telescope/observatory data, spectroscopy, photometry, simulations, LaTeX, Jupyter notebooks, or scientific visualization.
• Experience leading or supporting remote teams of researchers, educators, reviewers, annotators, science writers, or QAs.
• Experience with AI training, data annotation, LLM evaluation, scientific QA, academic review, or rubric-based review.
Company:
Our Core mission is to develop, deploy, or integrate artificial intelligence (AI) — including machine learning (ML), data analytics, automation, natural language processing (NLP), computer vision, and related technologies — to solve real-world problems, improve decision-making, automate repetitive tasks, and deliver intelligent solutions across industries. Founded in 2018, the company is headquartered in Abu Dhabi, Abu Dhabi Emirate, AE, , with a team of 51-200 employees. The company is currently Growth Stage.
YO IT Consulting is a fast-growing AI Data Services company delivering training data for many of the world’s largest AI companies and foundation-model labs. They are seeking an Astronomer Quality Assurance Lead to oversee quality and consistency in astronomy and astrophysics AI training projects, ensuring that all contributions meet the expected standards of accuracy and clarity.
Responsibilities:
• Quality monitoring: Spot-check astronomy/astrophysics items, identify quality issues, provide ongoing feedback through DMs, and escalate recurring or critical issues.
• Scientific review: Evaluate AI-generated astronomy/astrophysics explanations, calculations, diagrams, observational interpretations, comparisons, and step-by-step reasoning for accuracy and clarity.
• Trainer and QA communication: Update trainers and QAs on Discord about new item guidelines, project changes, workflow updates, quality expectations, and astronomy/astrophysics-specific review standards.
• Question handling: Respond to trainer/QA questions clearly and promptly, especially around physical assumptions, units, astronomical terminology, observational methods, formulas, and rubric interpretation.
• Trainer/QA activation management: DM contributors who are inactive or not working, encourage activation, track follow-ups, and flag availability issues when needed.
• Documentation: Create and maintain astronomy/astrophysics project documentation, including style guides, trackers, FAQs, quality notes, examples, honeypots, calibration tasks, and onboarding materials.
• Onboarding and training: Schedule and run onboarding/training calls with trainers and QAs to explain project expectations, workflows, rubrics, quality standards, and astronomy/astrophysics-specific review requirements.
• Quality alignment: Ensure all trainers and QAs apply astronomy/astrophysics review guidelines consistently and understand updates as projects evolve.
• Risk review: Flag misleading, overconfident, physically impossible, numerically incorrect, or poorly sourced astronomy/astrophysics claims.
• Process improvement: Identify recurring quality gaps, propose workflow improvements, and help build scalable QA processes for astronomy/astrophysics AI training projects.
Qualifications:
Required:
• Bachelor’s, Master’s, or PhD degree in Astronomy, Astrophysics, Physics, Space Science, Planetary Science, Cosmology, or a closely related field.
• Strong grasp of the English language to follow project guidelines, communicate with teams, and provide clear written feedback.
• 3+ years of experience in astronomy/astrophysics research, teaching, science communication, academic review, data analysis, observatory work, or related scientific workflows.
• Strong understanding of celestial mechanics, stellar evolution, galaxies, cosmology, electromagnetic radiation, observational methods, spectroscopy, planetary systems, black holes, and scientific uncertainty.
• Ability to evaluate astronomy/astrophysics content against detailed rubrics and identify issues such as incorrect physical assumptions, wrong units, flawed calculations, hallucinated facts, misleading explanations, or oversimplified conclusions.
• Comfortable working in fast-moving remote environments using tools such as Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems.
• Highly detail-oriented and organized, with the ability to maintain style guides, FAQs, trackers, onboarding materials, calibration tasks, and documentation.
Preferred:
• Familiarity with tools or methods such as Python, astronomical datasets, telescope/observatory data, spectroscopy, photometry, simulations, LaTeX, Jupyter notebooks, or scientific visualization.
• Experience leading or supporting remote teams of researchers, educators, reviewers, annotators, science writers, or QAs.
• Experience with AI training, data annotation, LLM evaluation, scientific QA, academic review, or rubric-based review.
Company:
Our Core mission is to develop, deploy, or integrate artificial intelligence (AI) — including machine learning (ML), data analytics, automation, natural language processing (NLP), computer vision, and related technologies — to solve real-world problems, improve decision-making, automate repetitive tasks, and deliver intelligent solutions across industries. Founded in 2018, the company is headquartered in Abu Dhabi, Abu Dhabi Emirate, AE, , with a team of 51-200 employees. The company is currently Growth Stage.