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Remote Ai Data Scientist Jobs (NOW HIRING)

GDIT

AI Data Scientist

Los Angeles, CA · On-site +1

Data Science and Data Engineering Job Qualifications: Skills: AI Systems, Big Data, Datasets ... a remote work model GDIT IS YOUR PLACE At GDIT, the mission is our purpose, and our people are at ...

GDIT

AI Data Scientist

Bossier City, LA · On-site +1

Data Science and Data Engineering Job Qualifications: Skills: AI Systems, Big Data, Datasets ... a remote work model GDIT IS YOUR PLACE At GDIT, the mission is our purpose, and our people are at ...

Apex Informatics

AI Data Scientist

AI Data Scientist Duration : 9 months Telecommute : yes Travel : no Primary Responsibilities: • Able to write a concept paper can take it from idea to implementation • Partner with Engineering ...

Instant Serve LLC

AI Data Architect /REMOTE

Denver, CO · Remote

$75 - $80/hr

Remote AI Data Architect - Public Sector Location: Preferably Colorado Duration: 6 months We are seeking a forward-thinking AI Data Architect to lead data-driven initiatives in the public sector.

Geisinger Health

AI Data Scientist Senior

Danville, PA · On-site +1

Facilitates data-driven decision-making by effectively communicating the value and impact of AI models. * Mentors and guide junior data scientists, fostering their professional growth and technical ...

Geisinger Health

AI Data Scientist Senior

Danville, PA · On-site +1

Facilitates data-driven decision-making by effectively communicating the value and impact of AI models. * Mentors and guide junior data scientists, fostering their professional growth and technical ...

CSAA

This Data Scientist role offers the opportunity to help CSAA Insurance Group anticipate and prepare ... Deep knowledge in AI, data mining, data evaluation, and proficiency in compiling an effective and ...

CSAA

This Data Scientist role offers the opportunity to help CSAA Insurance Group anticipate and prepare ... Deep knowledge in AI, data mining, data evaluation, and proficiency in compiling an effective and ...

CSAA

This Data Scientist role offers the opportunity to help CSAA Insurance Group anticipate and prepare ... Deep knowledge in AI, data mining, data evaluation, and proficiency in compiling an effective and ...

CSAA

This Data Scientist role offers the opportunity to help CSAA Insurance Group anticipate and prepare ... Deep knowledge in AI, data mining, data evaluation, and proficiency in compiling an effective and ...

CSAA

This Data Scientist role offers the opportunity to help CSAA Insurance Group anticipate and prepare ... Deep knowledge in AI, data mining, data evaluation, and proficiency in compiling an effective and ...

CSAA

This Data Scientist role offers the opportunity to help CSAA Insurance Group anticipate and prepare ... Deep knowledge in AI, data mining, data evaluation, and proficiency in compiling an effective and ...

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All JobsAi Data Scientist JobsRemote Ai Data Scientist Jobs

Remote Ai Data Scientist information

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$37.5K

$122.7K

$196.5K

How much do remote ai data scientist jobs pay per year?

As of Jul 27, 2026, the average yearly pay for remote ai data scientist in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What are some common challenges faced by remote AI Data Scientists, and how can they be overcome?

Remote AI Data Scientists often encounter challenges such as collaborating effectively with cross-functional teams across different time zones and maintaining consistent communication to align on project goals. Additionally, access to large datasets and high-performance computing resources can sometimes be limited outside a traditional office setting. These challenges can be managed by leveraging robust collaboration tools, ensuring clear documentation, and proactively scheduling regular check-ins. Building a disciplined work routine and staying connected with the broader data science community can also support professional growth and project success.

What is the difference between Remote Ai Data Scientist vs Remote Machine Learning Engineer?

AspectRemote Ai Data ScientistRemote Machine Learning Engineer
Required CredentialsDegree in Data Science, AI, or related fields; proficiency in Python, R, SQLDegree in Computer Science, AI, or related; strong programming skills in Python, Java, or C++
Work EnvironmentData analysis, model development, research in cloud or remote settingsModel deployment, system optimization, software engineering in remote teams
Employer & Industry UsageTech companies, startups, research institutionsTech firms, AI product companies, software development firms

While both roles involve AI and data, Remote Ai Data Scientists focus on analyzing data and developing AI models, whereas Remote Machine Learning Engineers primarily implement, optimize, and deploy these models in production environments. The roles often overlap but differ in their core responsibilities and skill emphasis.

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

To thrive as a Remote AI Data Scientist, you need a strong background in statistics, machine learning, data analysis, and programming (typically Python or R), often supported by a degree in computer science, mathematics, or a related field. Familiarity with tools such as TensorFlow, PyTorch, SQL, cloud platforms (e.g., AWS, Azure), and relevant certifications like AWS Certified Machine Learning or Google Professional Data Engineer is highly valuable. Excellent problem-solving, communication, and self-management skills distinguish top performers, especially in remote work environments. These competencies ensure effective model development, collaborative teamwork, and the ability to deliver impactful AI solutions from any location.

What is a Remote AI Data Scientist?

A Remote AI Data Scientist is a professional who develops and applies artificial intelligence and machine learning models to analyze data and solve business problems, all while working from a location outside a traditional office environment. They use programming languages, statistical methods, and data engineering tools to extract insights and build predictive models. Remote AI Data Scientists often collaborate with cross-functional teams using online communication and project management tools. This role offers flexibility in work location and hours while requiring strong self-motivation and communication skills to succeed in a virtual setting.
More about Remote Ai Data Scientist jobs
What cities are hiring for Remote Ai Data Scientist jobs? Cities with the most Remote Ai Data Scientist job openings:
What are the most commonly searched types of Ai Data Scientist jobs? The most popular types of Ai Data Scientist jobs are:
What states have the most Remote Ai Data Scientist jobs? States with the most job openings for Remote Ai Data Scientist jobs include:
What job categories do people searching Remote Ai Data Scientist jobs look for? The top searched job categories for Remote Ai Data Scientist jobs are:
Remote Ai Data Scientist jobs near you
Infographic showing various Remote Ai Data Scientist job openings in the United States as of July 2026, with employment types broken down into 60% Full Time, 10% Part Time, 10% Temporary, and 20% Contract. Highlights an 100% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.

Principal AI Data Scientist

MSR Technology Group

Phoenix, AZ • Remote

Full-time

Posted 13 days ago

Job description


Infomatics is partnered with a large retailer that is hiring a Principal AI Data Scientist on a direct hire/FTE basis near Phoenix, AZ. Can work remote. All applicants must be eligible & willing to be hired on W2.

You will lead various AI efforts involving computer vision, deep learning, and nlp in addition to other machine learning model builds. You will not only work on large scale projects to provide value to the customers but are also routinely involved in building our internal R&D capability to have an edge in the analytics industry. You will lead some of the most strategic and very complex problems.
Duties/Responsibilities:
  • Builds and validates machine learning models of high risk/reward problems utilizing large scale data from multiple data sources and methodologies.
  • Uses machine learning techniques to create data-driven solutions for various business use-cases.
  • Writes programs utilizing existing libraries and methodologies.
  • Interprets, communicates, and presents analytic results to C-Level executives and below.
  • Consistently collaborates with fellow data scientists, data engineers, business partners, project managers, cross-functional teams, key stakeholders, and other domains to drive business value.
  • Leads AI best practice sharing opportunities and knowledge of industry trends and innovations in data science.
  • Leads projects with external partners and vendors to develop solutions to meet business needs while resolving any issues that may arise.
  • Contributes to the organization's data strategy and roadmap.
  • Embeds and drives the organization with the most up-to-date AI methodology.
Qualifications:
  • Master's or PhD degree in a quantitative field with 5+ years of data science experience.
  • Applied expertise in artificial intelligence with experience applying natural language processing, computer vision (image processing), and deep leaning. Need to have the capability to leverage current mature mainstream AI application tools and methodology
  • Proficiency in machine learning with familiarity and actual applications of scikit-learn library machine learning techniques such as decision tree, gradient boosting, XGBoost, etc. for regression, classification, or segmentation problems.
  • Programming expertise in Python with familiarity with cloud environments (AWS, Databricks, etc.)
  • Ability to work with large data sets from multiple data sources
  • Ability to communicate complex analytics concepts and techniques to C-Level executives and below
  • Ability to work collaboratively with other data scientists, data engineers, multiple stakeholders across the business, and with external partners
  • Intellectual curiosity, a passion for data, and a results orientation.