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Internship Data Science Physics Jobs in Virginia

Senior Data Scientist

Alexandria, VA · Hybrid

$131K - $237K/yr

As a Senior Data Scientist, you will : * Lead the design, development, and deployment of advanced ... Science, Mathematics, Statistics, Engineering, Physics, Computational Social Science, etc.

The Data Scientist II is responsible for collecting data and using wide range of data science ... physics, engineering, finance or computer science) Graduate's degree preferred with either ...

A minimum of a Bachelor's Degree in Engineering, Physics, Computer Science, or a related discipline, with relevant coursework in data science, machine learning, and/or artificial intelligence. * A ...

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Internship Data Science Physics information

What are the key skills and qualifications needed to thrive as an Internship Data Science Physics, and why are they important?

To thrive as an Internship Data Science Physics, you need a solid grounding in physics, mathematics, and programming, typically supported by progress toward a relevant degree. Familiarity with data analysis tools such as Python, MATLAB, or R, and experience using statistical or machine learning libraries are commonly expected. Strong problem-solving, analytical thinking, and effective communication skills help interns stand out in team-based research environments. These competencies ensure you can effectively analyze complex data, contribute to scientific discoveries, and present insights clearly.

What is the difference between Internship Data Science Physics vs Data Analyst Intern?

AspectInternship Data Science PhysicsData Analyst Intern
Required SkillsProgramming, data analysis, physics concepts, statistical methodsData analysis, Excel, SQL, visualization tools
Work EnvironmentResearch labs, tech companies, academiaBusiness, finance, marketing departments
Industry UsageResearch, scientific computing, tech innovationBusiness intelligence, reporting, decision-making

Internship Data Science Physics focuses on applying data science skills within physics and research contexts, often involving scientific computing and experimental data. In contrast, Data Analyst Internships are centered on analyzing business data, creating reports, and supporting decision-making processes. Both roles require analytical skills and familiarity with data tools, but their environments and applications differ significantly.

What types of projects or tasks can I expect to work on during a Data Science Physics internship?

As a Data Science Physics intern, you can expect to work on projects that involve analyzing large datasets derived from physical experiments or simulations, developing predictive models, and visualizing complex phenomena. Typical tasks might include cleaning and preprocessing data, applying statistical or machine learning techniques, and collaborating with researchers to interpret results. You may also assist in automating data workflows or contributing to scientific publications, providing a dynamic and collaborative environment that bridges data science and physics.

What are Internship Data Science Physics positions?

Internship Data Science Physics positions are temporary roles designed for students or recent graduates with a background in physics who are interested in applying data science techniques to solve scientific and analytical problems. These internships typically involve working with large datasets, performing statistical analyses, building models, and interpreting results within a physics-related context. Interns gain hands-on experience with programming languages like Python or R, machine learning tools, and data visualization methods, often contributing to research or product development teams. These roles help bridge academic knowledge in physics with practical data science skills, preparing interns for careers in research, technology, or industry.
What are the most commonly searched types of Data Science Physics jobs in Virginia? The most popular types of Data Science Physics jobs in Virginia are:
What cities in Virginia are hiring for Internship Data Science Physics jobs? Cities in Virginia with the most Internship Data Science Physics job openings:
Data Scientist (SME) - TS/SCI with Polygraph Required

Data Scientist (SME) - TS/SCI with Polygraph Required

LMI

Mclean, VA

Full-time

Re-posted 7 days ago


Job description

LMI is a new breed of digital solutions provider dedicated to accelerating government impact with innovation and speed. Investing in technology and prototypes ahead of need, LMI brings commercial-grade platforms and mission-ready AI to federal agencies at commercial speed.


Leveraging our mission-ready technology and solutions, proven expertise in federal deployment, and strategic relationships, we enhance outcomes for the government, efficiently and effectively. With a focus on agility and collaboration, LMI serves the defense, space, healthcare, and energy sectors—helping agencies navigate complexity and outpace change. Headquartered in Tysons, Virginia, LMI is committed to delivering impactful results that strengthen missions and drive lasting value.

Position is on the research staff of a government consulting organization and will be based out of Reston, VA. This position provides verified mathematical and scientific techniques programmatically to answer questions prioritized by the Sponsor.


  • Work with a project-based team comprised of staff and other contractors.
  • Work closely with the Sponsor to review and track data science requirements and provide regular status updates.
  • Consult with customers to determine present and future user needs for Sponsor consideration.
  • Utilize project management systems such as a Content Management System (CMS) (e.g. Wordpress), Confluence and JIRA to define and track requirements.
  • Engage frequently with customers and stakeholders to clearly explain the project status and results in both written and verbal or multimedia briefings. 
  • Provide traceability within program documents and the overall computing environment and architecture.
  • Implement data science requirements, to include data engineering and data analytics services as defined by the Sponsor.
  • Use the full software lifecycle to create data science products which include data ingestion, analytics which may include machine learning, and some form of output as either a machine-readable format (e.g. file output, database output, standard/streaming output) or a user interface or dashboard.
  • Develop robust data engineering pipelines utilizing Apache Nifi and Python to include use and development of REST APIs and microservices.
  • Clean, parse and transform data from multiple file types into appropriate database architecture (e.g. SQL, noSQL, graph) which performs at scale.
  • Develop self-guided training curriculum which includes detailed Jupyter Notebooks and documentation about how to use open-source and commercial software and Sponsor-developed data science software.
  • Develop, deploy and provide feature enhancements using Python for data science products and services, to include Python packages, code documentation, notebooks, and microservices.

Required
  • Bachelor’s Degree in a quantitative discipline (e.g., related discipline)
  • Minimum 6-8 years experience
  • Demonstrated experience programming with Python.
  • Demonstrated experience with general Linux computing and advanced bash scripting.
  • Demonstrated experience constructing complex multi-data source queries with database technologies such as PostgreSQL, MySQL, Neo4J or RDS.
  • Demonstrated experience processing data sources containing structured or unstructured data.
  • Demonstrated experience developing data pipelines with NiFi to bring data into a central environment.
  • Demonstrated experience delivering results to stakeholders through written documentation and oral briefings.
  • Demonstrated experience using code repositories such as Git.
  • Demonstrated experience using Elastic and Kibana technologies.
  • Demonstrated experience working with multiple stakeholders.
  • Demonstrated experience documenting such artifacts as code, Python packages and methodologies.
  • Demonstrated experience using Jupyter Notebooks.
  • Demonstrated experience with machine learning techniques including natural language processing.
  • Demonstrated experience explaining complex technical issues to more junior data scientists, in graphical, verbal, or written formats.
  • Demonstrated experience developing tested, reusable and reproducible work.
  • Work or educational background in one or more of the following areas: mathematics, statistics, hard sciences (e.g. Physics, Computational Biology, Astronomy, Neuroscience, etc.) computer science, data science, or business analytics.
  • Must possess TS/SCI with polygraph.
Desired
  • Demonstrated experience with system configurations, development and design, specifically around enterprise systems.
  • Demonstrated experience communicating both verbally and in writing, when responding to emails, telephone calls and/or in person inquiries from organizational personnel.
  • Certification:
    • ISACA Certified Information Security Manager (CISM)
    • ISACA Certified Information Systems Auditor (CISA)
    • ISC Certified Information Systems Security Professional (CISSP)
    • ISC Certified Cloud Security Professional (CCSP)
    • ISC Certified Authorization Professional (CAP)

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Target salary range: $104,040 - $183,600. Final compensation will be determined by a variety of factors including but not limited to your skills, experience, education, and/or certifications.

The salary range displayed represents the typical salary range for this position and is not a guarantee of compensation. Individual salaries are determined by various factors including, but not limited to location, internal equity, business considerations, client contract requirements, and candidate qualifications, such as education, experience, skills, and security clearances.

Applicants must meet eligibility requirements for a U.S. Government security clearance. Only US Citizens are eligible for a security clearance. For this position, LMI will only consider applicants with security clearances or applicants who are eligible for security clearances, due to the nature of the work.


US-VA-McLean