ZipRecruiter

Log In

2

Remote Data Science Astronomy Jobs (NOW HIRING)

Adidev Technologies Inc

Data Science

San Francisco, CA · Remote

As a Data Scientist/Data Science Specialist for Adidev Technologies Inc., you will be enhancing and ... Remote Sensing Science, Environmental Sciences, Computational Astronomy or related scientific ...

Rebellion Defenses

Remote Data Scientist

Jackson, MS · On-site +1

Proven experience in data science or a related field. * Proficiency in programming languages such ... Strong communication skills and the ability to work collaboratively in a remote environment. Salary ...

Premise Health

Data Science Analyst - Remote

Brentwood, TN · On-site +1

$75K - $87K/yr

This is a Full Time, remote, Data Science Analyst role. What You'll Do * Analysis, Model Development & AI Solutions: * Perform exploratory data analysis to identify patterns and opportunities in ...

Adidev Technologies Inc

DATA SCIENTIST

Austin, TX · Remote

As a Data Scientist/Data Science Specialist for Adidev Technologies Inc., you will be enhancing and ... Remote Sensing Science, Environmental Sciences, Computational Astronomy or related scientific ...

next page

Showing results 1-20

All JobsRemote Data Science Astronomy Jobs

Remote Data Science Astronomy information

Can data science jobs be done remotely?

Data science jobs, including roles in astronomy, are often performed remotely, especially when tasks involve data analysis, coding, and modeling that can be done with a computer and internet access. Many companies and organizations offer remote positions for data scientists, requiring skills in programming languages like Python or R and familiarity with cloud-based tools. However, some roles may require on-site collaboration or access to specialized equipment, depending on the nature of the work.

What is the 80 20 rule in data science?

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

Is data science used in astronomy?

Data science is extensively used in astronomy, with data scientists analyzing large datasets from telescopes and space missions to identify patterns and make discoveries. Skills in machine learning, statistical analysis, and programming tools like Python and R are commonly applied in this field.

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 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 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 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.

Does NASA hire data scientists?

Yes, NASA hires data scientists to analyze large datasets related to space missions, climate, and astrophysics. These roles often require skills in programming, statistical analysis, and experience with tools like Python, R, or SQL, and may involve working on research projects or mission support. Data scientists at NASA contribute to scientific discoveries and technological advancements in space exploration.
More about Remote Data Science Astronomy jobs
What cities are hiring for Remote Data Science Astronomy jobs? Cities with the most Remote Data Science Astronomy job openings:
What are the most commonly searched types of Data Science Astronomy jobs? The most popular types of Data Science Astronomy jobs are:
What states have the most Remote Data Science Astronomy jobs? States with the most job openings for Remote Data Science Astronomy jobs include:
What job categories do people searching Remote Data Science Astronomy jobs look for? The top searched job categories for Remote Data Science Astronomy jobs are:
Remote Data Science Astronomy jobs near you
Infographic showing various Remote Data Science Astronomy job openings in the United States as of June 2026, with employment types broken down into 80% Full Time, and 20% Part Time. Highlights an 100% Remote job distribution.
Data Science

Data Science

Adidev Technologies Inc

San Francisco, CA • Remote

Full-time

Posted 28 days ago

Job description

Adidev Technologies Inc 

www.adidevtechnologies.com

URGENT HIRE - HIRING PROCESS - 24-48 HOURS!

Adidev Technologies is seeking 1-2 yrs of relevant experience in Data Science. A project can last anywhere from 6 months to 18 months. Salary varies depending on experience, and we are in search of candidates looking to start as soon as possible. Excellent written and oral communication are required as is the ability to work well in a team environment.

If you are looking for a new challenge and are ready to make an impact on a growing team, then this will be a perfect fit. As a Data Scientist/Data Science Specialist for Adidev Technologies Inc., you will be enhancing and debugging large-scale applications for one of our well-known clients.

Adidev Technologies is a growing software consulting company that is constantly expanding. As we are working with renowned clients and ready to take on new ones, we are seeking brilliant software engineers. Not only do we offer a great team to work with, but we also offer you an opportunity to make an immediate impact and get rewarded accordingly

 

Job Description

  • Demonstrated experience using machine learning, deep learning, statistical methodology, and simulation/optimization modeling in geospatial, network topography, recommendation systems, environmental systems, and/or agronomic problems.
  • Strong foundation in Python programming in a cloud environment.
  • Strong quantitative abilities, distinctive problem-solving, and excellent analysis skills
  • Expertise in data wrangling using SQL,
  • Practical knowledge and experience with cloud-computing systems and platforms, including the routine deployment of pipelines through Kubernetes
  • Fluency in querying/extracting/aggregating data via SQL scripting.
  • Extract, load and transform data (ETL) from structured and unstructured sources
  • Apply Natural Language Processing and Computer Vision to solve business use cases,
  • Strong skills in scientific data analyses, modeling, visualization and communication of results.
  • Knowledge of Python libraries (NumPy, Pandas, SciKit-Learn, TensorFlow, PyTorch), Spacy, MongoDB, PostgreSQL, Flask, streamlet and a good knowledge of data pipelines construction
  • Ph.D., M.S. or B.S. in Computer Science, Computational Physics, Operations Research, Geospatial Sciences, Remote Sensing Science, Environmental Sciences, Computational Astronomy or related scientific discipline


Must  have 

  • Understanding of various machine learning algorithms (e.g. SVM, Random Forests, Gradient Boosting, Log-Log regression, XGBoost, Lasso, Ridge, Clustering techniques, Neural Networks and others)
  • Regression (e.g. ? Linear/Logistic/MNL/Mixed Effects/Regularization)
  • Classification (K-means, Hierarchical, Latent Class, DBScan, SVM)
  • Dimension Reduction techniques (Principal Component analysis, Singular Value Decomposition etc.)
  • Optimization (Linear programming, Stochastic Gradient Descent, Genetic Algorithm etc.)
  • Experience with neural network approaches to text classification CNN, RNN, LSTM,Keras
  • Machine Learning algorithms? Neural Networks, Naïve Bayes, Bagging & Boosting, Random Forest
  • Distributed computing tools and cloud technology (AWS)

QUALIFICATIONS

  • Degree in Data Science, Computer Science, Engineering, Math, or Statistics preferred

  • At least 2 yrs of relevant experience in Data Science


SKILLS

  • SQL, statistical modeling, Feature engineering, Data visualization, Deploying models to production, Python programming, AWS, Domains(Healthcare/ Manufacturing/ Marketing/ Financial/ Telecommunication), powerbi/tableau, data warehouse

Benefits

  • Competitive Salary

  • Paid Relocation

  • Remote Support

  • Guaranteed Regular Salary Reviews

  • Job Type: W2 or Contract 1099 (full-time - 40 hours)

Employment Type: FULL_TIME

Apply