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Intern Python Data Analyst Jobs in Maryland (NOW HIRING)

Proficiency with data management and analysis tools such as SQL, Python, Excel, Access, or equivalent technologies. * Experience supporting enterprise data repositories, storage environments, or data ...

Proficiency with data management and analysis tools such as SQL, Python, Excel, Access, or equivalent technologies. * Experience supporting enterprise data repositories, storage environments, or data ...

$62K - $141K/yr

Experience with Python including Pandas, NumPy, API integration, SQL, ETL, and ELT * Ability to brief senior leaders * Ability to c onduct quantitative and qualitative analysis of data to identify ...

New

Strong working proficiency in Python for data analysis (e.g., pandas, SciPy, Jupyter, matplotlib/Plotly or similar). * A solid grounding in regression analysis and applied statistics from a data ...

Showing results 41-60

Intern Python Data Analyst information

What does an Intern Python Data Analyst do?

An Intern Python Data Analyst assists in collecting, processing, and analyzing data using Python programming language. They support the data team by writing scripts to clean and visualize data, and help generate insights from large datasets. Interns also learn to use data analysis libraries such as pandas, NumPy, and matplotlib, and may assist with reporting or automation tasks. This role is typically entry-level and offers hands-on experience in data analysis within a supervised environment.

What are the key skills and qualifications needed to thrive as an Intern Python Data Analyst?

To thrive as an Intern Python Data Analyst, you need a solid understanding of data analysis concepts, proficiency in Python, and familiarity with statistics, typically supported by coursework in data science or a related field. Experience using tools like pandas, NumPy, Jupyter Notebook, and SQL, as well as exposure to data visualization libraries such as matplotlib or seaborn, is highly beneficial. Curiosity, attention to detail, and strong problem-solving and communication skills help you extract insights and present findings effectively. These skills are important for accurately analyzing data, translating results into actionable insights, and supporting data-driven decisions within an organization.

What types of projects and tasks can an Intern Python Data Analyst expect to work on during their internship?

As an Intern Python Data Analyst, you can expect to work on a variety of data-driven projects, such as cleaning and preparing datasets, creating data visualizations, and running exploratory data analysis using Python libraries like pandas and matplotlib. You'll likely support senior analysts by automating data collection processes and helping to generate regular reports. Collaboration with team members from different departments is common, as you'll need to understand business needs and present your findings in a clear, actionable way. These experiences provide valuable exposure to real-world data challenges and can help you develop both technical and communication skills crucial for advancing in data analytics.

What is the difference between Intern Python Data Analyst vs Intern Data Scientist?

AspectIntern Python Data AnalystIntern Data Scientist
Required SkillsPython, SQL, Excel, Data VisualizationPython, R, Machine Learning, Statistical Analysis
Work EnvironmentData analysis, reporting, dashboardsModel development, predictive analytics, research
Industry UsageBusiness intelligence, finance, marketingTech, healthcare, research institutions

Intern Python Data Analysts focus on analyzing data, creating reports, and visualizations using Python and related tools. Intern Data Scientists work on building models, applying machine learning, and conducting advanced statistical analysis. While both roles require Python skills, Data Scientists typically need additional knowledge of R and machine learning techniques. The roles often overlap in industries like tech and finance, but Data Scientists tend to engage in more complex predictive tasks, whereas Data Analysts focus on interpreting data for business insights.

What are the most commonly searched types of Python Data Analyst jobs in Maryland?

The most popular types of Python Data Analyst jobs in Maryland are:

What cities in Maryland are hiring for Intern Python Data Analyst jobs?

Cities in Maryland with the most Intern Python Data Analyst job openings:

Journeyman Data Analyst

Leidos

Bethesda, MD • On-site

Full-time

Retirement, PTO

Re-posted 12 days ago


Leidos rating

8.3

Company rating: 8.3 out of 10

Based on 152 frontline employees who took The Breakroom Quiz

79th of 496 rated business services


Job description

Leidos has a new and exciting opportunity for a Journeyman Data Analyst in our Intel Sector Analysis Solutions Business Area (ASBA). Our talented team is at the forefront in Security Engineering, Computer Network Operations (CNO), Mission Software, Analytical Methods and Modeling, Signals Intelligence (SIGINT), and Cryptographic Key Management. At Leidos, we offer competitive benefits, including Paid Time Off, 11 paid Holidays, 401K with a 6% company match and immediate vesting, Flexible Schedules, Discounted Stock Purchase Plans, Technical Upskilling, Education and Training Support, Parental Paid Leave, and much more. Join us and make a difference in Analysis Solutions!

Must have an active TS/SCI Polygraph up front (this is firm).

Job Description:

Seeking a Data Analyst to support our customer onsite in Bethesda, MD. The Data Analyst will support enterprise data management, integration, governance, and configuration management activities across the program. This role is responsible for ensuring enterprise data is structured, accessible, reliable, and aligned with mission and operational objectives as data volume, complexity, and interoperability requirements continue to evolve.

The successful candidate will establish and maintain data lifecycle processes, support integration and interoperability across systems, and assist with implementing data standards, governance policies, and repository management practices. This position will also support configuration management efforts through controlled reviews of technical and engineering documentation to ensure consistency, traceability, and version control across enterprise data assets and systems.

Key Responsibilities

  • Establish, maintain, and improve enterprise data lifecycle processes, including data ingestion, storage, usage, archival, and retention practices.

  • Support enterprise data governance initiatives by defining and maintaining data standards, validation rules, metadata management practices, and quality control procedures.

  • Integrate disparate data sources and artifacts across federated systems to support interoperability and mission requirements.

  • Support the development, maintenance, and optimization of enterprise data repositories and storage environments.

  • Conduct data quality assessments and implement standardized processes to improve data reliability and minimize manual intervention.

  • Perform configuration management and controlled documentation reviews to ensure alignment, traceability, consistency, and version control across data assets and engineering documentation.

  • Analyze enterprise data structures, policies, and workflows to identify opportunities for improved accessibility, efficiency, and reliability.

  • Develop and maintain documentation, reports, briefing materials, and technical artifacts related to data governance, repository management, and integration activities.

  • Support integration of new data models, standards, schemas, and artifacts into existing enterprise environments.

  • Collaborate with engineering, operations, and stakeholder teams to support evolving mission and program data requirements.

  • Provide recommendations to improve enterprise data architecture, governance policies, interoperability standards, and repository performance.

  • Communicate technical findings and recommendations clearly through written documentation, visual presentations, and verbal briefings suitable for both technical and non-technical audiences.

Basic Qualifications

  • Requires BA/BS and 8+ years of experience supporting data management, data governance, data integration, or enterprise data environments; or no degree and 12+ years of relevant experience.

  • TS/SCI with Polygraph clearance required.

  • Experience supporting enterprise data lifecycle management processes and data governance initiatives.

  • Experience with data integration, interoperability, metadata management, and repository administration.

  • Knowledge of configuration management principles, version control practices, and documentation governance.

  • Experience developing and maintaining technical documentation, reports, and briefing materials.

  • Proficiency with data management and analysis tools such as SQL, Python, Excel, Access, or equivalent technologies.

  • Experience supporting enterprise data repositories, storage environments, or data management platforms.

  • Ability to analyze data-related processes and recommend improvements to data quality, accessibility, and operational efficiency.

  • Strong written and verbal communication skills with the ability to present technical concepts to diverse stakeholder audiences.

Preferred Qualifications

  • Experience supporting Intelligence Community programs or other federal government environments.

  • Familiarity with data governance frameworks, metadata standards, and enterprise data management best practices.

  • Hands-on experience with Jira, Confluence, or other collaboration and configuration management tools.

  • Experience supporting cloud-based data environments and enterprise storage architectures.

  • Familiarity with automation processes that improve data validation, ingestion, and reporting workflows.

  • Experience supporting configuration control boards, technical review processes, or engineering documentation management.

  • Understanding of enterprise interoperability standards and data exchange methodologies.

  • Experience with the following Work Products preferred:

    • Data Management Lifecycle Documentation

    • Data Governance and Quality Plans

    • Data Integration and Interoperability Plans

    • Data Repository and Infrastructure Documentation

    • Configuration Management and Documentation Review Reports

    • Data Standards and Architecture Recommendations

    • Data Performance and Reliability Reports

#ASBA

If you're looking for comfort, keep scrolling. At Leidos, we outthink, outbuild, and outpace the status quo - because the mission demands it. We're not hiring followers. We're recruiting the ones who disrupt, provoke, and refuse to fail. Step 10 is ancient history. We're already at step 30 - and moving faster than anyone else dares.

Original Posting:July 6, 2026

For U.S. Positions: While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.

Pay Range:Pay Range $92,300.00 - $166,850.00

The Leidos pay range for this job level is a general guideline onlyand not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.


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About Leidos

Sourced by ZipRecruiter

At Leidos, we deliver innovative solutions through the efforts of our diverse and talented people who are dedicated to our customers' success. We empower our teams, contribute to our communities, and operate sustainable practices. Everything we do is built on a commitment to do the right thing for our customers, our people, and our community.

Industry

It services

Company size

10,000+ Employees

Headquarters location

Reston, VA, US

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