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Data Science Machine Learning Jobs in Virginia (NOW HIRING)

Thomson Reuters

Data Scientist

Mclean, VA · On-site +1

Strong command of Python and common data science and machine learning libraries * Hands-on experience with modern ML/AI techniques, including LLMs, MLLMs, NLP, embeddings, and related approaches

THOMSON REUTERS

Data Scientist

Mclean, VA

Strong command of Python and common data science and machine learning libraries * Hands-on experience with modern ML/AI techniques, including LLMs, MLLMs, NLP, embeddings, and related approaches

Unissant

Data Scientist

Herndon, VA · On-site

$104K - $163K/yr

Work Experience and Job Skills: * 3+ years of experience in data science, machine learning, advanced analytics, or related analytical disciplines, preferably supporting federal law enforcement, DHS ...

RIVIDIUM

Data Scientist- Senior

Quantico, VA

Stay current with emerging trends in data science, machine learning, and artificial intelligence Minimum Qualifications * Bachelor?s or Master?s degree in Computer Science, Data Science, Statistics ...

RiVidium, Inc

Data Scientist- Senior

Quantico, VA · On-site

Stay current with emerging trends in data science, machine learning, and artificial intelligence Minimum Qualifications * Bachelor's or Master's degree in Computer Science, Data Science, Statistics ...

NT Concepts

Data Scientist

Herndon, VA · On-site +1

Contribute to solutioning sessions and technical sections of project proposals Required Qualifications * 5+ years of experience in data science, machine learning, or a related field * Hands-on ...

Guidehouse

AI/ML Data Scientist

Arlington, VA · On-site

A minimum of FOUR (4) years of experience in data science, machine learning, or applied analytics roles * U.S. Citizenship required and ability to obtain and maintain a Public Trust clearance.

Guidehouse

AI/ML Data Scientist

Arlington, VA

A minimum of FOUR (4) years of experience in data science, machine learning, or applied analytics roles * U.S. Citizenship required and ability to obtain and maintain a Public Trust clearance.

Guidehouse

AI/ML Data Scientist

Arlington, VA · On-site

$113K - $188K/yr

A minimum of 4 years of experience in data science, machine learning, or applied analytics roles * U.S. Citizenship required and ability to obtain and maintain a Public Trust clearance. * Experience ...

NALLEY CONSULTING

Data Scientist - Mid

Reston, VA · On-site

Responsibilities : • Provide data science, machine learning, and artificial intelligence support. • Conduct data engineering tasks to integrate multiple APIs, and support process automation, data ...

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Showing results 1-20

All JobsData Science Machine Learning JobsData Science Machine Learning Jobs in Virginia

Data Science Machine Learning information

See Virginia salary details

$37.2K

$121.7K

$194.8K

How much do data science machine learning jobs pay per year?

As of Jul 22, 2026, the average yearly pay for data science machine learning in Virginia is $121,686.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,700.00 and $134,800.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Data Science Machine Learning professional, and why are they important?

To thrive as a Data Science Machine Learning professional, you need a strong background in statistics, programming (usually Python or R), and a solid understanding of machine learning algorithms, often supported by a degree in computer science, mathematics, or a related field. Familiarity with tools like TensorFlow, scikit-learn, SQL databases, and cloud platforms, as well as certifications such as AWS Certified Machine Learning, are typically valuable. Critical thinking, problem-solving, and effective communication are vital soft skills for interpreting data and collaborating with stakeholders. These skills enable professionals to develop robust models, extract actionable insights, and drive data-driven decision-making in organizations.

What are some common challenges faced when deploying machine learning models as a Data Science Machine Learning professional?

A frequent challenge in this role is bridging the gap between building accurate models in a controlled environment and deploying them effectively in production systems. Issues such as data drift, model performance degradation, and integration with existing IT infrastructure often arise. Collaboration with engineering and IT teams is crucial to ensure models are scalable, maintainable, and secure. Regular monitoring and updating of deployed models are also essential responsibilities to sustain their value to the business.

What is the difference between Data Science Machine Learning vs Data Analyst?

AspectData Science Machine LearningData Analyst
Required SkillsProgramming (Python, R), statistics, machine learning algorithmsData visualization, SQL, basic statistics
Work EnvironmentDeveloping models, coding, experimenting with algorithmsData reporting, dashboard creation, data cleaning
Industry UsageTech, finance, healthcare, where predictive models are neededBusiness intelligence, marketing, operations

Data Science Machine Learning professionals focus on building predictive models and algorithms using programming and advanced statistics, often working on complex projects. Data Analysts primarily interpret data through visualization and reporting to support business decisions. While both roles require data skills, Data Science Machine Learning involves more technical programming and modeling, whereas Data Analysts focus on data interpretation and presentation.

What is data science machine learning?

Data science machine learning refers to the use of algorithms and statistical models to analyze and draw insights from complex data sets. In this field, professionals use machine learning techniques to build predictive models, automate decision-making processes, and uncover patterns in data. Machine learning is a core component of data science, enabling systems to improve their performance over time without being explicitly programmed. Data scientists with machine learning expertise are in high demand across industries like healthcare, finance, and technology.
What cities in Virginia are hiring for Data Science Machine Learning jobs? Cities in Virginia with the most Data Science Machine Learning job openings:
Data Science Machine Learning jobs near you
Infographic showing various Data Science Machine Learning job openings in Virginia as of July 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, 1% Temporary, and 3% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $121,686 per year, or $58.5 per hour.

Machine Learning (ML) Engineer

Velocity-X, LLC

Chantilly, VA • On-site

Full-time

Posted 7 days ago

Job description

About Velocity-X:
Velocity-X, a VelocityBlack company, constructs and deploys data management and analytics solutions for the defense and intelligence communities. We’re proud to boast a world-class engineering team that thrives on rolling up their sleeves to solve your mission’s biggest challenges.

Velocity-X is seeking a highly motivated and self-directed professional to fill the role of Machine Learning (ML) Engineer to support our team in Northern Virginia.

Responsibilities:

  • Design, develop, and implement machine learning models and algorithms to solve specific business problems.
  • Build and maintain scalable and robust machine learning pipelines for data ingestion, preprocessing, feature engineering, model training, evaluation, and deployment.
  • Transform machine learning models into deployable APIs and integrate them with existing applications and infrastructure.
  • Collaborate closely with data scientists, software engineers, and product managers to understand requirements and translate them into practical ML solutions.
  • Experiment with different machine learning techniques and algorithms to identify the most effective approaches for given problems.
  • Evaluate model performance using appropriate metrics and iterate on models to improve accuracy, efficiency, and scalability.
  • Monitor and maintain deployed models, ensuring their reliability and performance in production environments.
  • Troubleshoot and resolve issues related to machine learning models and pipelines.
  • Stay up-to-date with the latest advancements in machine learning, deep learning, and related fields.
  • Contribute to the development of best practices and standards for machine learning development and deployment within the team.
  • Document machine learning models, experiments, and deployment processes.
  • Potentially work with large datasets and big data technologies.
  • Optimize machine learning models for performance and efficiency.

Qualifications:

  • Master’s in computer science, Machine Learning, or higher level degree is preferred with of 3+ years of related industry experience in Machine Learning, Computer Science, Data Science or related fields.
  • Demonstrated hands-on experience in developing and deploying machine learning models in a production environment.
  • Strong programming skills in Python and experience with relevant machine learning libraries and frameworks such as TensorFlow, Keras, PyTorch, scikit-learn, etc.
  • Solid understanding of machine learning algorithms (e.g., regression, classification, clusting, dimensionality reduction, deep learning architectures).
  • Experience with data preprocessing, feature engineering, and data visualization techniques.
  • Familiarity with data storage and processing technologies (e.g., SQL, NoSQL databases, Spark, Hadoop).
  • Experience with cloud platforms (e.g., AWS, Azure, GCP) and their machine learning services.
  • Understanding of software development principles, version control (e.g., Git), and CI/CD pipelines.
  • Strong analytical and problem-solving skills with the ability to interpret data and draw meaningful conclusions.
  • Excellent communication and collaboration skills to effectively communicate technical concepts to both technical and non-technical audiences.

Preferred Skills:

  • Experience with specific areas of machine learning such as Natural Language Processing (NLP), Computer Vision, or Recommender Systems.
  • Experience with MLOps practices and tools for automating and monitoring machine learning workflows.
  • Knowledge of containerization technologies like Docker and orchestration tools like Kubernetes.
  • Experience with building and deploying RESTful APIs.
  • Familiarity with big data technologies and distributed computing.
  • Experience with statistical modeling and inference.

Position Clearance Requirement:

TS/SCI with Full-Scope Polygraph

Equal Opportunity Employer:

Velocity-X is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national origin, gender, sexual orientation, gender identity, age, physical or mental disability, genetic factors, military/veteran status or other characteristics protected by law.