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Python Data Analysis Internship Jobs in Philadelphia, PA

SANS

Python Data Engineer

Philadelphia, PA · On-site

Write production-grade Python for data processing and integration between on-prem and cloud systems ... Track record owning delivery end to end, from data analysis and architecture through production ...

Athenago

Data Science Intern

Wilmington, DE

Analyze large and diverse datasets (e.g. client requirements, XP performance metrics) to uncover ... Proficiency in programming languages and data tools such as Python (with libraries like pandas ...

Winaxis

Lead II - Data Analysis

Philadelphia, PA · On-site

... and Python (pandas, numpy, etc.) for data analysis and scripting. - Strong analytical and problem-solving skills; able to manipulate and analyze large datasets to derive actionable insights ...

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Python Data Analysis Internship information

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$42

How much do python data analysis internship jobs pay per hour?

As of Jul 11, 2026, the average hourly pay for python data analysis internship in Philadelphia, PA is $22.71, according to ZipRecruiter salary data. Most workers in this role earn between $17.45 and $24.76 per hour, depending on experience, location, and employer.

What is a Python Data Analysis Internship?

A Python Data Analysis Internship is a temporary position, often for students or recent graduates, that provides hands-on experience in analyzing data using the Python programming language. Interns typically assist with collecting, cleaning, and interpreting large datasets, using Python libraries such as pandas, NumPy, and matplotlib. The internship is designed to help participants develop practical skills in data manipulation, statistical analysis, and data visualization. It is a great way to gain real-world experience in data science and analytics while building a professional network.

What are the key skills and qualifications needed to thrive as a Python Data Analysis Intern, and why are they important?

To thrive as a Python Data Analysis Intern, you need a solid understanding of statistics, data manipulation, and Python programming, often supported by relevant coursework or projects. Familiarity with tools such as pandas, NumPy, Jupyter Notebook, and data visualization libraries like matplotlib or seaborn is typically required. Strong analytical thinking, attention to detail, and effective communication skills help interns interpret data and share insights clearly with team members. These skills enable interns to extract actionable insights from complex datasets and effectively contribute to data-driven decision making.

What is the difference between Python Data Analysis Internship vs Data Analyst?

AspectPython Data Analysis InternshipData Analyst
Required SkillsPython, data analysis, basic statisticsData analysis, SQL, Excel, Python (optional)
Work EnvironmentInternship setting, learning-focusedFull-time or part-time professional role
Experience LevelEntry-level, internshipEntry to mid-level professional
Industry UsageInternship programs, entry rolesBusiness, finance, tech, healthcare

While a Python Data Analysis Internship focuses on gaining hands-on experience with Python and data analysis tools in an internship setting, a Data Analyst role involves applying these skills professionally to analyze data, generate reports, and support decision-making in various industries.

What types of projects and tasks can I expect to work on during a Python Data Analysis Internship?

As a Python Data Analysis intern, you can typically expect to work on projects involving data collection, cleaning, and exploration using Python libraries such as Pandas and NumPy. Your daily tasks may include writing scripts to automate data processing, creating visualizations with tools like Matplotlib or Seaborn, and assisting in preparing reports or presentations based on your findings. Interns often collaborate with data scientists, analysts, and sometimes other departments to support ongoing projects and gain exposure to real-world data challenges. This hands-on experience is valuable for building both technical skills and an understanding of how data-driven decisions are made in a professional environment.
What are the most commonly searched types of Python Data Analysis jobs in Philadelphia, PA? The most popular types of Python Data Analysis jobs in Philadelphia, PA are:
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What cities near Philadelphia, PA are hiring for Python Data Analysis Internship jobs? Cities near Philadelphia, PA with the most Python Data Analysis Internship job openings:
Python Data Analysis Internship jobs near you
Infographic showing various Python Data Analysis Internship job openings in Philadelphia, PA as of July 2026, with employment types broken down into 76% Full Time, 22% Part Time, and 2% Contract. Highlights an 81% Physical, 5% Hybrid, and 14% Remote job distribution, with an average salary of $47,235 per year, or $22.7 per hour.

Python Data Engineer

SANS

Philadelphia, PA • On-site

Other

Posted 5 days ago

Job description


Client is placing a senior data integration consultant embedded at a financial services client. The consultant works onsite as part of the client's data engineering effort, integrating the client's systems and data sources with Client's Declarative Agentic Framework (DAF) and connected products.
This is delivery work, not advisory. The consultant owns the data pipelines, warehouse structures, and integration points that the deployment depends on, and is accountable for data quality and reliability in production.
What the Consultant Will Do

  • Design and build data integration pipelines connecting client source systems (reference data, pricing, transaction, custody, or similar) to client's AI's platform .
  • Own data warehouse and data lake architecture for the engagement, including ingestion, transformation, and data quality rules.
  • Work hands-on with ETL tooling (Informatica, Snowflake, or equivalent) and cloud data platforms (AWS or Azure).
  • Write production-grade Python for data processing and integration between on-prem and cloud systems.
  • Define data reconciliation and data lineage processes so the client can trust what the pipelines produce.
  • Coordinate with the client's data engineering, ops, and compliance stakeholders, and with client's AI's deployment team.
  • Document architecture decisions and integration patterns so the work is defensible and repeatable across future deployments.

Required Background

  • 10+ years in enterprise data architecture, data engineering, or solution architecture roles.
  • Direct experience in financial services, ideally capital markets, asset management, or securities operations. Candidate should recognize terms like reference data, corporate actions, and reconciliation without explanation.
  • Hands-on ETL and data warehousing expertise: Informatica, Snowflake , or comparable enterprise-grade tooling .
  • Production Python for data pipelines and integration work , not scripting on the side.
  • Experience with REST APIs, message queues (Kafka or similar), and containerized deployments (Docker).
  • Track record owning delivery end to end, from data analysis and architecture through production support, ideally with distributed or offshore team coordination.
  • Comfortable being the senior technical presence in the room with client stakeholders from day one. No ramp-up period.

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