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Freelance Applied Scientist Machine Learning Jobs in Springfield, VA

Qualtrics

Senior Applied Scientist

Reston, VA · On-site

$95K - $130K/yr

Applied scientists partner with application teams to deliver algorithms and models that drive ... Leverage your deep knowledge of AI principles, including machine learning, natural language ...

Qualtrics

Senior Applied Scientist

Reston, VA · On-site

$95K - $130K/yr

Applied scientists partner with application teams to deliver algorithms and models that drive ... Leverage your deep knowledge of AI principles, including machine learning, natural language ...

Parsons

Machine Learning / Data Scientist

Washington, DC · On-site

$88K - $154K/yr

We have a career opportunity for a Machine Learning / Data Scientist to develop advanced analytical models and experiments that enhance decision-making, improve forecasting, and uncover insights ...

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All JobsApplied Scientist Machine Learning JobsFreelance Applied Scientist Machine Learning JobsFreelance Applied Scientist Machine Learning Jobs in Springfield, VA

Freelance Applied Scientist Machine Learning information

How do freelance applied scientists in machine learning typically collaborate with clients and teams remotely?

Freelance applied scientists in machine learning often work remotely, communicating with clients and teams through regular video calls, messaging platforms, and project management tools. Collaboration usually involves understanding client requirements, clarifying data needs, and providing frequent updates on project progress. Since projects may require input from software engineers, data analysts, or product managers, strong communication skills and the ability to document work clearly are crucial. Freelancers also need to proactively manage their schedules and expectations, as they frequently juggle multiple projects or stakeholders at once.

What are the key skills and qualifications needed to thrive as a freelance applied scientist in machine learning?

To excel as a Freelance Applied Scientist in Machine Learning, you need a solid background in mathematics, statistics, and computer science, typically supported by an advanced degree and strong programming skills in Python or similar languages. Familiarity with machine learning frameworks (such as TensorFlow or PyTorch), cloud platforms, and data analysis tools is essential, along with relevant certifications like TensorFlow Developer or AWS Machine Learning. Strong problem-solving abilities, self-motivation, and effective communication are crucial for managing projects independently and collaborating with diverse clients. These skills enable successful delivery of high-impact solutions tailored to client needs, ensuring both technical excellence and client satisfaction.

What does a freelance applied scientist in machine learning do?

A Freelance Applied Scientist in Machine Learning is a professional who independently works with clients or organizations to design, develop, and implement machine learning models and solutions. Their responsibilities typically include data analysis, building predictive models, and translating business problems into data-driven solutions. They may also be involved in researching new algorithms, optimizing existing models, and communicating findings to stakeholders. Since they work on a freelance basis, they often manage multiple projects and clients simultaneously.

What is the difference between Freelance Applied Scientist Machine Learning vs Freelance Data Scientist?

AspectFreelance Applied Scientist Machine LearningFreelance Data Scientist
CredentialsAdvanced degrees in ML, AI, or related fieldsDegrees in Data Science, Statistics, or related fields
Work EnvironmentFocus on developing ML models, algorithms, and AI solutionsData analysis, visualization, and statistical modeling
Industry UsageUsed in AI-driven products, research, and advanced analyticsApplied in business insights, reporting, and data-driven decision making

Freelance Applied Scientist Machine Learning professionals specialize in developing and deploying machine learning models and AI solutions, often requiring advanced technical credentials. Freelance Data Scientists focus on analyzing data, creating reports, and deriving insights, with a broader scope of statistical skills. Both roles are in high demand but serve different purposes within data and AI projects.

What job categories do people searching Freelance Applied Scientist Machine Learning jobs in Springfield, VA look for? The top searched job categories for Freelance Applied Scientist Machine Learning jobs in Springfield, VA are:
What cities near Springfield, VA are hiring for Freelance Applied Scientist Machine Learning jobs? Cities near Springfield, VA with the most Freelance Applied Scientist Machine Learning job openings:
Freelance Applied Scientist Machine Learning jobs near you
Infographic showing various Freelance Applied Scientist Machine Learning job openings in Springfield, VA as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Senior Data Scientist / Machine Learning Engineer

Waypoint Human Capital

Mclean, VA • On-site

Full-time

Posted 7 days ago

Job description

Position Title: Senior Data Scientist / Machine Learning Engineer
Position Type: Full-Time, On-Site
Position Location: Tysons, VA
Clearance Required: Active TS/SCI with CI Polygraph or Full Scope Polygraph
Waypoint's client is seeking a dynamic Senior Data Scientist / Machine Learning Engineer with an active TS/SCI CI Poly or higher to join their team. The Senior Data Scientist / Machine Learning Engineer will work directly with data scientists, software engineers, and subject matter experts in the definition of new analytics capabilities able to provide federal customers with the information they need to make proper decisions and enable their digital transformation.
This position works directly with data scientists, software engineers, and subject matter experts to research, design, and deploy machine learning algorithms that support federal customers in digital transformation and data-driven decision making. They will contribute to new analytics capabilities and assist customers in building their own applications. This position requires a bachelor's degree in Computer Science, Electrical Engineering, Statistics, or a related field, 5 to 10 years of relevant experience, and strong Python and applied ML skills. An active TS/SCI with CI Polygraph or Full Scope Polygraph is required.
Responsibilities
The responsibilities include, but are not limited to:
  • Research, design, implement, and deploy Machine Learning algorithms for enterprise applications.
  • Assist and enable federal customers to build their own applications.
  • Contribute to the design and implementation of new features.

Required
  • Active Top Secret clearance with CI Polygraph or Full Scope Polygraph.
  • Bachelor's degree in Computer Science, Electrical Engineering, Statistics, or equivalent fields required.
  • MS or PhD in Computer Science, Electrical Engineering, Statistics, or equivalent fields preferred.
  • Minimum 5–10 years relevant work experience preferred.
  • Excellent programming skills in Python.
  • Applied Machine Learning experience (regression and classification, supervised, and unsupervised learning).
  • Strong mathematical background (linear algebra, calculus, probability, and statistics).
  • Experience with scalable Machine Learning (MapReduce, streaming).
  • Ability to drive a project and work both independently and in a team.
  • Smart, motivated, can-do attitude, and seeks to make a difference.
  • Excellent verbal and written communication skills.
  • Passion for developing team-oriented solutions to complex engineering problems.
  • Thrive in an autonomous, empowering, and exciting environment.
  • Ability to collaborate across multiple functional teams to improve scalability.
  • Ability to convey highly technical concepts and information in written form to both technical and non-technical audiences.
  • Ability to work on multiple concurrent projects.
  • Strong self-motivation and the ability to work with minimal supervision.
  • Team-oriented, energetic, results- and delivery-focused, with a strong commitment to quality and meeting deadlines.
  • Ability to work in an Agile environment.

Desired
  • Hands-on experience deploying and operating applications using IaaS and PaaS on major cloud providers, including Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP).
  • Proficient in leveraging modern LLM tools to accelerate development workflows and enhance code quality.
  • Experience with deep learning.
  • Experience with natural language processing (NLP).
  • Experience with computer vision.
  • Experience with reinforcement learning.