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Intern Data Scientist Machine Learning Jobs in Washington

Parsons

Machine Learning / Data Scientist

Washington, DC · On-site

$88K - $154K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

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 ...

Accroid Inc

Data Scientist

Springfield, VA · On-site

Data Scientist (Active TS/SCI Clearance) Top Mandatory Skills * 8+ years of experience in Data Science, Machine Learning, or Analytics * Strong foundation in Statistics, Probability, Graph Theory, or ...

KDA Consulting Inc

Data Scientist

Mclean, VA · On-site

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

KDA Consulting Inc

Data Scientist

Chantilly, VA · On-site

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

KDA Consulting Inc

Data Scientist

Chantilly, VA · On-site

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

KDA Consulting Inc

Data Scientist

Herndon, VA · On-site

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

Cmu

Data Scientist

Arlington, VA · On-site

Data Scientists at the SEI use advanced statistics, data analytics, machine learning, and artificial intelligence to help our government and industry clients research and solve cybersecurity ...

Markon

Data Scientist - AI/Machine Learning

Annapolis Junction, MD · On-site

$150K - $210K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Apply machine learning techniques to identify and transform data features, find hidden patterns and ... Collaborate with Data Scientists to develop processes and tools to monitor and analyze model ...

Leidos

Data Scientist

Springfield, VA · On-site

Develop and validate machine learning models for classification, regression, clustering, anomaly detection, ranking, recommendation, and pattern discovery. * Architect end-to-end analytic workflows ...

Leidos

Data Scientist

Springfield, VA · On-site

Develop and validate machine learning models for classification, regression, clustering, anomaly detection, ranking, recommendation, and pattern discovery. * Architect end-to-end analytic workflows ...

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All JobsIntern Data Scientist Machine Learning JobsIntern Data Scientist Machine Learning Jobs in Washington

Intern Data Scientist Machine Learning information

What types of projects and responsibilities can an intern data scientist machine learning expect to work on?

As an Intern Data Scientist focused on Machine Learning, you will often assist in tasks such as data cleaning, feature engineering, and developing or testing machine learning models under the supervision of senior team members. You may also be involved in exploratory data analysis and help interpret model results to provide actionable insights. Interns typically collaborate closely with data engineers, analysts, and software developers, gaining exposure to end-to-end machine learning pipelines. This hands-on experience provides valuable learning opportunities and helps build the foundational skills needed for future roles in data science.

What are the key skills and qualifications needed to thrive as an intern data scientist machine learning, and why are they important?

To thrive as an Intern Data Scientist (Machine Learning), you need a solid understanding of statistics, programming skills (typically in Python or R), and foundational knowledge of machine learning algorithms, often supported by coursework or relevant projects. Familiarity with tools like scikit-learn, TensorFlow, Jupyter notebooks, and version control systems (e.g., Git) is commonly expected. Strong analytical thinking, curiosity, and effective communication skills help you interpret data insights and work collaboratively within a team. These abilities are crucial for translating data into actionable solutions and contributing to impactful machine learning projects.

What does an intern data scientist machine learning do?

An Intern Data Scientist in Machine Learning assists in analyzing large datasets, building predictive models, and extracting insights to support business decisions. They often work under the guidance of experienced data scientists to clean data, implement machine learning algorithms, and evaluate model performance. Their responsibilities may also include data visualization and reporting findings to team members. This role provides hands-on experience with real-world data science problems and tools, helping interns develop essential technical and analytical skills.

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

AspectIntern Data Scientist Machine LearningIntern Data Analyst
Required SkillsBasic programming, statistics, machine learning conceptsData analysis, Excel, SQL, visualization tools
Work EnvironmentResearch-focused, model development, algorithm testingData cleaning, reporting, dashboard creation
Common Industry UsageTech, finance, healthcareRetail, marketing, finance

Intern Data Scientist Machine Learning roles focus on developing and testing machine learning models, requiring knowledge of algorithms and programming. Intern Data Analyst positions emphasize data cleaning, analysis, and visualization. Both roles are entry-level but differ in technical depth and project focus, catering to different career paths within data-driven industries.

What are popular job titles related to Intern Data Scientist Machine Learning jobs in Washington? For Intern Data Scientist Machine Learning jobs in Washington, the most frequently searched job titles are:
What job categories do people searching Intern Data Scientist Machine Learning jobs in Washington look for? The top searched job categories for Intern Data Scientist Machine Learning jobs in Washington are:
What cities in Washington are hiring for Intern Data Scientist Machine Learning jobs? Cities in Washington with the most Intern Data Scientist Machine Learning job openings:
Intern Data Scientist Machine Learning jobs near you

Senior Data Scientist / Machine Learning Engineer

Waypoint Human Capital

Mclean, VA

Full-time

Posted 13 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.