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Remote Meta Data Science Jobs in Hampton, VA (NOW HIRING)

... clinical data sources. * Provide expert insights on structure-activity and structure-property ... Assess and review AI-generated outputs for scientific rigor, accuracy, and practical relevance ...

... clinical data sources. * Provide expert insights on structure-activity and structure-property ... Assess and review AI-generated outputs for scientific rigor, accuracy, and practical relevance ...

... clinical data sources. * Provide expert insights on structure-activity and structure-property ... Assess and review AI-generated outputs for scientific rigor, accuracy, and practical relevance ...

Remote micro1 is engaging Microbiologists to contribute their scientific expertise to a unique ... Document experimental findings and processes with a focus on clarity for AI training data.

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Remote Meta Data Science information

See Hampton, VA salary details

$36.2K

$118.6K

$189.9K

How much do remote meta data science jobs pay per year?

As of Aug 21, 2026, the average yearly pay for remote meta data science in Hampton, VA is $118,619.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,200.00 and $131,400.00 per year, depending on experience, location, and employer.

What is a remote meta data scientist?

A Remote Meta Data Scientist is a professional who works for Meta (formerly Facebook) in the field of data science, but does so from a remote location instead of a traditional office. They analyze large datasets, build predictive models, and provide insights to help Meta improve its products and user experience. Their work may involve machine learning, statistical analysis, and collaborating virtually with cross-functional teams. Remote Meta Data Scientists use tools such as Python, SQL, and data visualization software to solve complex business problems.

How does a remote meta data science role typically collaborate with cross-functional teams despite being off-site?

In a remote Meta Data Science position, collaboration with cross-functional teams—such as product managers, engineers, and designers—is primarily facilitated through virtual communication tools like video conferencing, chat platforms, and collaborative project management software. Regular stand-ups, sprint meetings, and asynchronous updates help ensure alignment on project goals and timelines. While remote work offers flexibility, it also requires proactive communication and documentation to maintain transparency and foster effective teamwork. Building relationships remotely may take extra effort, but companies like Meta provide structured onboarding and virtual community events to support team cohesion.

What are the key skills and qualifications needed to thrive as a remote meta data scientist, and why are they important?

To thrive as a Remote Meta Data Scientist, you need strong analytical skills, expertise in statistics and machine learning, and a degree in a quantitative field such as computer science or mathematics. Proficiency with data science tools like Python, R, SQL, and platforms such as TensorFlow or PyTorch is typically required, along with experience using collaboration tools for remote work. Excellent communication, self-motivation, and problem-solving abilities are essential soft skills for remote collaboration and translating insights to stakeholders. These skills ensure you can independently deliver impactful data-driven solutions while effectively collaborating across distributed teams.

What is the difference between Remote Meta Data Science vs Remote Data Analyst?

AspectRemote Meta Data ScienceRemote Data Analyst
Required CredentialsBachelor's or higher in Data Science, Computer Science, or related fields; knowledge of programming languages like Python or RBachelor's degree in Statistics, Mathematics, or related fields; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentCollaborative remote teams, often with data science and engineering departmentsRemote work with focus on data reporting, visualization, and business insights
Employer & Industry UsageTech companies, e-commerce, finance, and healthcareMarketing agencies, retail, finance, and consulting firms

Remote Meta Data Science involves advanced data modeling, machine learning, and statistical analysis, often requiring programming skills and a strong technical background. Remote Data Analysts focus on interpreting data, creating reports, and visualizations to support business decisions. While both roles work remotely and require data handling skills, Meta Data Scientists typically engage in more complex modeling, whereas Data Analysts concentrate on data interpretation and presentation.

What are popular job titles related to Remote Meta Data Science jobs in Hampton, VA?

For Remote Meta Data Science jobs in Hampton, VA, the most frequently searched job titles are:

What job categories do people searching Remote Meta Data Science jobs in Hampton, VA look for?

The top searched job categories for Remote Meta Data Science jobs in Hampton, VA are:

What cities near Hampton, VA are hiring for Remote Meta Data Science jobs?

Cities near Hampton, VA with the most Remote Meta Data Science job openings:

Infographic showing various Remote Meta Data Science job openings in Hampton, VA as of June 2026, with employment types broken down into 1% As Needed, 87% Full Time, 9% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $118,619 per year, or $57 per hour.

Cheminformatics Specialist - Remote

micro1 AI

Suffolk, VA • Remote

$80 - $110/hr

Part-time

Posted 21 days ago


Job description

Role Title: Computational Biology & Cheminformatics Expert


Role Type: Contractor


Location: Remote


micro1 is engaging Computational Biology & Cheminformatics Experts to contribute their expertise to a customer’s computational drug discovery project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Scope of Work

  1. Analyze and interpret small-molecule and drug discovery datasets using advanced computational biology, bioinformatics, and cheminformatics methods.
  2. Curate, annotate, and validate chemical and biological datasets (e.g., ChEMBL, PubChem, DrugBank) to support AI-driven discovery platforms.
  3. Evaluate compound-target interactions, ADMET properties, and lead optimization strategies by integrating chemical, biological, and clinical data sources.
  4. Provide expert insights on structure-activity and structure-property relationships (SAR/SPR), medicinal chemistry approaches, and experimental design considerations.
  5. Build and implement code-based benchmark tasks (e.g., terminal/CLI-based environments) that reflect realistic computational drug discovery scenarios.
  6. Develop reproducible environments (e.g., using Docker) and automated testing pipelines to ensure task correctness and solvability.
  7. Assess and review AI-generated outputs for scientific rigor, accuracy, and practical relevance, delivering detailed written feedback and recommendations.


Preferred Qualifications

  1. Advanced expertise in Computational Biology, Cheminformatics, Medicinal Chemistry, Biochemistry, or related fields; advanced degree (PhD, MSc, PharmD) highly valued but not strictly required.
  2. Strong coding proficiency in Python (beyond analysis scripts), with hands-on experience building tools, pipelines, or testable code; familiarity with Git, GitHub, and Docker.
  3. Extensive experience with cheminformatics toolkits and platforms such as RDKit, KNIME, Schrödinger, OpenEye, or MOE.
  4. Proven track record in small-molecule drug discovery, SAR/QSAR evaluation, ADMET prediction, or virtual screening workflows.
  5. Comfort working with public chemical and bioactivity databases and integrating diverse datasets for scientific analysis.
  6. Demonstrated ability to clearly communicate complex chemical and biological concepts in written feedback and reports.
  7. Experience participating in multidisciplinary and/or remote projects; familiarity with AI-assisted coding tools is a plus.