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Full Time Data Scientist Machine Learning Jobs in Washington, DC

Data Scientists at the SEI use advanced statistics, data analytics, machine learning, and ... Full time/Part time Full time Pay Basis Salary More Information: * Please visit "Why Carnegie ...

Machine Learning & AI Development * Design, develop, and deploy machine learning models to solve complex mission problems * Build predictive and prescriptive analytics solutions to support ...

Machine Learning & AI Development * Design, develop, and deploy machine learning models to solve complex mission problems * Build predictive and prescriptive analytics solutions to support ...

Machine Learning & AI Development * Design, develop, and deploy machine learning models to solve complex mission problems * Build predictive and prescriptive analytics solutions to support ...

Machine Learning & AI Development * Design, develop, and deploy machine learning models to solve complex mission problems * Build predictive and prescriptive analytics solutions to support ...

Intelligence Time Type: Full time Minimum Clearance Required to Start: TS/SCI Employee Type ... The Data Scientist will leverage advanced analytics, machine learning, automation, and data fusion ...

Data Scientist

Chantilly, VA · On-site

$165K - $210K/yr

May use machine learning and statistical approaches based on the analysis of the dataset. May ... UNAVAILABLEEmployment Type: FULL_TIME

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Full Time Data Scientist Machine Learning information

See Washington, DC salary details

$42.5K

$139K

$222.6K

How much do full time data scientist machine learning jobs pay per year?

As of Aug 3, 2026, the average yearly pay for full time data scientist machine learning in Washington, DC is $139,013.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,600.00 and $154,000.00 per year, depending on experience, location, and employer.

What are some common challenges faced by full time data scientists specializing in machine learning, and how can they be addressed?

Full-time Data Scientists in Machine Learning often encounter challenges such as dealing with messy or incomplete data, tuning complex models for optimal performance, and effectively communicating technical insights to non-technical stakeholders. Addressing these challenges usually involves collaborating closely with data engineers to improve data quality, staying updated with the latest ML techniques, and developing strong communication skills to translate findings into actionable business strategies. Additionally, regular code reviews and participation in cross-functional meetings help ensure alignment and foster a supportive team environment.

What does a full time data scientist specializing in machine learning do?

A Full Time Data Scientist specializing in Machine Learning is responsible for analyzing large datasets to discover patterns and insights, and for building, testing, and deploying machine learning models to solve business problems. They use statistical techniques, programming skills, and domain knowledge to turn raw data into actionable information. Their day-to-day tasks often include data cleaning, feature engineering, model selection, and performance evaluation. They also collaborate with other teams to integrate machine learning solutions into products or decision-making processes. This role typically requires proficiency in languages like Python or R, and familiarity with tools such as TensorFlow, scikit-learn, or PyTorch.

What are the key skills and qualifications needed to thrive as a full time data scientist specializing in machine learning?

To thrive as a Full Time Data Scientist Machine Learning, you need strong analytical skills, expertise in statistics, machine learning techniques, and a relevant degree in computer science, mathematics, or a related field. Proficiency with programming languages such as Python or R, experience with machine learning libraries like TensorFlow or scikit-learn, and familiarity with data visualization and big data platforms are typically required. Critical thinking, problem-solving abilities, and effective communication are essential soft skills for collaborating with stakeholders and translating data insights into business value. These skills are crucial for developing robust models, interpreting complex data, and driving impactful, data-driven decisions within organizations.

What is the difference between Full Time Data Scientist Machine Learning vs Data Analyst?

AspectFull Time Data Scientist Machine LearningData Analyst
Required CredentialsBachelor's/Master's in Data Science, Computer Science, or related; knowledge of ML algorithmsBachelor's in Statistics, Mathematics, or related; proficiency in data visualization and SQL
Work EnvironmentDeveloping ML models, programming in Python/R, deploying algorithmsData cleaning, reporting, creating dashboards, analyzing datasets
Industry UsageTech, finance, healthcare, e-commerceRetail, marketing, finance, healthcare

Full Time Data Scientist Machine Learning roles focus on building and deploying machine learning models, requiring advanced programming and statistical skills. Data Analysts primarily interpret data, generate reports, and support decision-making with less emphasis on ML techniques. Both roles are vital but differ in technical depth and responsibilities.

What are the most commonly searched types of Data Scientist Machine Learning jobs in Washington, DC? The most popular types of Data Scientist Machine Learning jobs in Washington, DC are:

Senior Data Scientist / Machine Learning Engineer

Waypoint Human Capital

Mclean, VA

Full-time

Posted 3 days ago

New


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.