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Remote Data Science Astronomy Jobs in Gilbert, AZ

DataAnnotation

Decision Scientist

Phoenix, AZ · On-site +1

$40/hr

... remote work and setting your own schedule. We are looking for experienced quantitative ... Whether your background is in data science, astrophysics, economics, biostatistics, operations ...

Norstella

Senior Data Scientist

Phoenix, AZ · Remote

Remote, United States Date Posted: May 11, 2026 Employment Type: Full Time Job ID: R-1915 ... Job Summary Our dedicated Data Science team is at the forefront of revolutionizing pharma ...

DataAnnotation

Pricing Analyst - AI Trainer

Phoenix, AZ · On-site +1

$40/hr

... remote work and setting your own schedule. We are looking for experienced quantitative ... Whether your background is in data science, astrophysics, economics, biostatistics, operations ...

Varsity Tutors

Astronomy Tutor

Scottsdale, AZ · Remote

$40/hr

... data. Emphasizes quantitative reasoning about cosmic scales and connects astronomy to physics, mathematics, and the history of scientific discovery. * Curriculum Awareness & Adaptive Instruction:

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Remote Data Science Astronomy information

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

To thrive as a Remote Data Science Astronomer, you need a strong background in astrophysics, statistics, and data analysis, typically supported by a degree in astronomy, physics, or a related field. Proficiency with programming languages such as Python or R, experience with astronomical data processing tools (e.g., Astropy, IRAF), and familiarity with machine learning libraries are commonly required. Strong problem-solving skills, self-motivation, and effective communication are essential soft skills for collaborating remotely and interpreting complex data. These skills enable the accurate extraction of scientific insights from large datasets, drive research innovation, and ensure smooth coordination in distributed scientific teams.

What are some typical challenges faced by remote data science astronomers, and how can they be addressed?

Remote data science astronomers often face challenges related to accessing large datasets, collaborating effectively with distributed teams, and staying updated with the latest research tools. Utilizing cloud-based platforms and secure data-sharing protocols can help manage big astronomical datasets efficiently. Regular virtual meetings and clear communication channels are essential to maintain strong team collaboration. Additionally, participating in online workshops or communities can help remote astronomers stay current with new analytical methods and industry standards.

What is a Remote Data Science Astronomy job?

A Remote Data Science Astronomy job involves using data science techniques, such as statistical analysis, machine learning, and data visualization, to analyze astronomical data and solve problems in astronomy, all while working remotely. Professionals in this role process large datasets collected from telescopes or space missions to discover patterns, classify celestial objects, or make predictions about cosmic phenomena. This position typically requires strong programming skills, familiarity with astronomical datasets, and the ability to work independently from any location.

What is the difference between Remote Data Science Astronomy vs Remote Data Science Astrophysics?

AspectRemote Data Science AstronomyRemote Data Science Astrophysics
Required CredentialsBachelor's or Master's in Astronomy, Data Science, or related fieldsBachelor's or Master's in Astrophysics, Data Science, or related fields
Work EnvironmentResearch institutions, observatories, universities, or tech companiesResearch institutions, observatories, universities, or tech companies
Industry UsageAcademic research, space agencies, tech startups

Remote Data Science Astronomy and Remote Data Science Astrophysics share similar credentials and work environments, often involving research institutions and tech companies. The main difference lies in their focus: Astronomy emphasizes observational data and celestial phenomena, while Astrophysics concentrates on theoretical models and physical processes of celestial bodies. Both roles require strong data analysis skills and relevant educational backgrounds, making them closely related but distinct in their scientific emphasis.

What are popular job titles related to Remote Data Science Astronomy jobs in Gilbert, AZ? For Remote Data Science Astronomy jobs in Gilbert, AZ, the most frequently searched job titles are:
What job categories do people searching Remote Data Science Astronomy jobs in Gilbert, AZ look for? The top searched job categories for Remote Data Science Astronomy jobs in Gilbert, AZ are:
What cities near Gilbert, AZ are hiring for Remote Data Science Astronomy jobs? Cities near Gilbert, AZ with the most Remote Data Science Astronomy job openings:
Remote Data Science Astronomy jobs near you
Data Science Manager - AI Trainer

Data Science Manager - AI Trainer

DataAnnotation

Phoenix, AZ • On-site, Remote

$60/hr

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Join the DataAnnotation team and contribute to developing cutting‐edge AI systems, while enjoying the flexibility of remote work and setting your own schedule. We are looking for experienced quantitative professionals to help advance AI development. AI models are increasingly capable of performing complex analytical and scientific reasoning — but these systems still need practitioners with real‐world quantitative experience to validate whether the outputs actually hold up in practice.

That's where you come in. As a member of DataAnnotation's team, you'll work closely with state‐of‐the‐art AI models on tasks like evaluating AI‐generated quantitative analysis, solving technical problems, and providing feedback that directly shapes how these systems reason about data, models, and scientific problems. Whether your background is in data science, astrophysics, economics, biostatistics, operations research, or any other quantitative field, if you think rigorously about data and models, your skills are directly applicable here.

Some team members fit this work alongside a full‐time role, while others treat it as their primary focus. To get started, once you sign up for an account, you'll take a short assessment (this serves as our version of an interview). If you pass, you'll receive an email confirmation, and paid work will become available on our platform.

Benefits Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New Zealand. Flexible schedule: choose which projects you take on and when you work. Competitive pay: projects are paid hourly, up to $60 USD/hour.

Impact: help shape the future of AI systems built to reason about data and analytics. Responsibilities Evaluate AI‐generated quantitative work, including statistical analysis, predictive modeling, scientific reasoning, and data‐driven insights, for technical accuracy and real‐world validity. Design and solve quantitative problems used to train and benchmark AI systems, spanning areas like forecasting, experimental analysis, optimization, and statistical inference.

Write clear technical explanations and well‐documented analytical code. Provide feedback that directly shapes the next generation of AI models built for quantitative reasoning. Qualifications 2+ years of hands‐on experience in a quantitative role or research environment — such as data science, statistics, economics, finance, physics, biology, epidemiology, operations research, or any adjacent field.

Some coding experience required, with comfort writing and reviewing analytical code end‐to‐end. Practical experience with statistical methods, predictive modeling, and experiment design (e.g., A/B testing, hypothesis testing, regression, classification, time‐series forecasting). Fluency in English (native or bilingual level) with strong writing skills.

A bachelor's degree in a quantitative field is preferred (Statistics, Computer Science, Mathematics, Engineering, or similar); a master's or PhD is a plus. Relevant credentials are a plus (e.g., Kaggle Competition ranking, AWS/GCP ML certifications, or equivalent demonstrated expertise). Payment is made via PayPal.

We will never ask for any money from you. This job is only available to those in the US, Canada, UK, Ireland, Australia, and New Zealand. #J-18808-Ljbffr

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