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Ai Data Remote Jobs (NOW HIRING)

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AI Data Engineer

Boston, MA · On-site +1

$124K - $149K/yr

Flexible working arrangements (remote or hybrid options available). * The opportunity to work on ... AI and healthcare.

Digital Links Inc

AI & Data Engineer (W2)

Glen Lyn, VA · Remote

$117K - $140K/yr

Remote US, light travel may be required Employment Type: Contract-to-Hire (6 Months) Top Skills: RAG, Snowflake, SQL/Oracle, JSON/API's, Python/Java, AWS S3, CI/CD (Git/GitHub) Preferred Skills:

Alignment Healthcare

AI & Data Scientist (Remote)

Own end-to-end solutions: translate ambiguous healthcare and operational problems into AI/ML models that deliver measurable impact by selecting methods, building data/models, deploying services ...

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Ai Data Remote information

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

To thrive as an AI Data Remote Specialist, you need a solid understanding of data annotation, data analysis, and familiarity with AI concepts, typically supported by a relevant degree or prior experience in data-related fields. Proficiency with annotation tools, data management platforms, and basic programming languages like Python is often required. Attention to detail, time management, and strong communication skills are critical for accuracy and effective collaboration in a remote environment. These skills ensure high-quality, reliable data that is essential for training effective AI models and contributing to successful AI projects.

What is the difference between Ai Data Remote vs Data Analyst?

AspectAi Data RemoteData Analyst
Required CredentialsDegree in Data Science, AI, or related fields; programming skillsBachelor's in Statistics, Data Analysis, or related fields; analytical skills
Work EnvironmentRemote, often project-based or freelanceRemote or on-site, corporate or consulting settings
Industry UsageTech, AI startups, research firmsBusiness, finance, healthcare, marketing
Common Search/ComparisonYesNo

Ai Data Remote roles focus on developing and applying AI models and algorithms remotely, requiring specialized technical skills. Data Analysts interpret data to inform business decisions, often in a broader range of industries. While both roles involve data, Ai Data Remote positions are more technical and AI-specific, whereas Data Analysts focus on data interpretation and reporting.

What are some common challenges faced by AI Data professionals working remotely, and how can they be addressed?

AI Data professionals working remotely often face challenges such as coordinating with distributed teams, ensuring data security, and maintaining clear communication with stakeholders. To address these, it's important to establish regular check-ins, use secure data transfer tools, and leverage collaborative project management platforms. Additionally, setting clear expectations and documentation standards helps minimize misunderstandings and keeps projects on track.

What are AI Data Remote jobs?

AI Data Remote jobs involve working with artificial intelligence (AI) data tasks from a remote location, often from home. These roles typically include data labeling, data annotation, data analysis, and data management to help train and improve AI models. Employees in these positions may review, organize, and categorize large datasets, ensuring that the information used by AI systems is accurate and relevant. Remote AI data jobs are popular because they offer flexibility and the opportunity to work for companies across the globe.
More about Ai Data Remote jobs
What cities are hiring for Ai Data Remote jobs? Cities with the most Ai Data Remote job openings:
What states have the most Ai Data Remote jobs? States with the most job openings for Ai Data Remote jobs include:
What job categories do people searching Ai Data Remote jobs look for? The top searched job categories for Ai Data Remote jobs are:
Ai Data Remote jobs near you
Infographic showing various Ai Data Remote job openings in the United States as of July 2026, with employment types broken down into 75% Full Time, 22% Part Time, and 3% Contract. Highlights an 66% Physical, 3% Hybrid, and 31% Remote job distribution.

Principal AI Data Scientist

MSR Technology Group

Phoenix, AZ • Remote

Full-time

Re-posted 29 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.