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Phd Science Jobs in Virginia (NOW HIRING)

Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or related field (PhD preferred for some roles) * 5+ years of experience in data science or a related field

Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or related field (PhD preferred for some roles) * 5+ years of experience in data science or a related field

Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or related field (PhD preferred for some roles) * 5+ years of experience in data science or a related field

Showing results 21-40

Phd Science information

See Virginia salary details

$24.3K

$48K

$78.3K

How much do phd science jobs pay per year?

As of Aug 19, 2026, the average yearly pay for phd science in Virginia is $47,976.00, according to ZipRecruiter salary data. Most workers in this role earn between $38,200.00 and $51,600.00 per year, depending on experience, location, and employer.

What is a PhD in science?

A PhD in Science is the highest academic degree awarded in scientific fields such as biology, chemistry, physics, or environmental science. It typically involves several years of advanced coursework, followed by original research that contributes new knowledge to the field. Graduates must defend a dissertation before a panel of experts. Earning a PhD in Science prepares individuals for careers in academia, research, industry, and leadership roles within scientific organizations.

What are the key skills and qualifications needed to thrive as a PhD scientist?

To thrive as a PhD Scientist, you need advanced expertise in your scientific discipline, strong research skills, and a doctoral degree (PhD) in a relevant field. Familiarity with specialized laboratory equipment, data analysis software (such as R or Python), and publication processes is typically required. Critical thinking, attention to detail, and effective communication are vital soft skills for presenting complex findings and collaborating with peers. These skills and qualifications are crucial for driving innovative research, producing publishable results, and contributing to scientific advancement.

What are the typical career advancement paths for someone with a PhD in science in academia and industry?

Individuals with a PhD in Science often start in postdoctoral or entry-level research positions, where they build specialized expertise and publish their findings. In academia, advancement typically involves progressing to assistant, associate, and full professor roles, with additional opportunities to lead research groups or departments. In industry, PhD holders can move into senior scientist, project manager, or R&D director roles, with the potential to transition into leadership, policy, or consulting positions. Building a strong professional network, publishing impactful research, and developing leadership skills are key to advancing in both sectors.

What is the difference between Phd Science vs Data Scientist?

AspectPhd ScienceData Scientist
Required CredentialsPhD in a scientific field, research experienceBachelor's or Master's in CS, stats, or related field; often a PhD preferred
Work EnvironmentResearch labs, academia, industry R&DTech companies, finance, healthcare, consulting
Industry UsageResearch roles, scientific analysis, product developmentData analysis, machine learning, predictive modeling

While both roles involve analytical skills and data handling, Phd Science focuses on scientific research and experimentation, often in academic or R&D settings. Data Scientists primarily analyze large datasets to inform business decisions and develop models in industry environments. The key difference lies in their application areas and typical work environments.

Is a PhD worth it in science?

A PhD in science is valuable for careers in research, academia, and specialized industry roles that require advanced expertise and critical thinking skills. However, it often involves several years of study and research, and job prospects can vary depending on the field and geographic location. The decision to pursue a PhD should consider personal career goals and the demand for advanced scientific skills in the job market.

What can a PhD in science get you?

A PhD in science can lead to careers in research, academia, industry, or government, often involving roles such as scientist, researcher, or professor. It demonstrates advanced expertise and critical thinking skills, and may require additional certifications or experience depending on the field and position.

What is the salary of a PhD scientist?

The salary of a PhD scientist varies depending on the industry, experience, and location, but typically ranges from $70,000 to over $120,000 annually. Advanced skills, research experience, and specialized knowledge can lead to higher compensation, especially in biotech, pharmaceuticals, or research institutions.

What jobs can I do with a PhD in science?

A PhD in science qualifies individuals for research scientist, university professor, laboratory manager, or scientific consultant roles. These positions often require strong analytical skills, familiarity with laboratory tools, and the ability to conduct independent research or teach at higher education institutions.

What cities in Virginia are hiring for Phd Science jobs?

Cities in Virginia with the most Phd Science job openings:

Infographic showing various Phd Science job openings in Virginia as of August 2026, with employment types broken down into 1% As Needed, 70% Full Time, 27% Part Time, and 2% Contract. Highlights an 73% Physical, 4% Hybrid, and 23% Remote job distribution, with an average salary of $47,976 per year, or $23.1 per hour.

Full-time

Re-posted 28 days ago


Job description

Overview

VTG is seeking a highly analytical and driven Data Scientist with at least 5 years of experience leveraging data to drive business insights and decision-making. The ideal candidate will have strong expertise in statistical analysis, machine learning, and data modeling, with the ability to translate complex data into actionable insights.


What will you do?
  • Analyze large, complex datasets to identify trends, patterns, and actionable insights
  • Develop, train, and validate machine learning and statistical models
  • Design and implement experiments, including A/B testing and predictive analytics
  • Collaborate with data engineers and analysts to ensure data quality and accessibility
  • Communicate findings and recommendations to technical and non-technical stakeholders
  • Build data visualizations and dashboards to present insights effectively
  • Deploy and monitor machine learning models in production environments
  • Continuously improve model performance and accuracy
  • Stay current with emerging data science techniques, tools, and technologies

Do you have what it takes?
  • Active TS/SCI with Polygraph required.
  • Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or related field (PhD preferred for some roles)
  • 5+ years of experience in data science or a related field
  • Strong proficiency in programming languages such as Python or R
  • Experience with machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch)
  • Strong foundation in statistics, probability, and data analysis techniques
  • Experience with SQL and working with large datasets
  • Experience with data visualization tools (e.g., Tableau, Power BI, Matplotlib, Seaborn)
  • Familiarity with cloud platforms (AWS, Azure, or GCP)
Qualifications:
  • Active TS/SCI with Polygraph required.
  • Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or related field (PhD preferred for some roles)
  • 5+ years of experience in data science or a related field
  • Strong proficiency in programming languages such as Python or R
  • Experience with machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch)
  • Strong foundation in statistics, probability, and data analysis techniques
  • Experience with SQL and working with large datasets
  • Experience with data visualization tools (e.g., Tableau, Power BI, Matplotlib, Seaborn)
  • Familiarity with cloud platforms (AWS, Azure, or GCP)
Education:UNAVAILABLEEmployment Type: FULL_TIME