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Python Data Analysis Internship Jobs in Libertyville, IL

Swift Hire LLC

Senior Software Engineer(Python)

Chicago, IL · On-site

$126K - $166K/yr

Title - Senior Software Engineer(Python) Senior Software Engineer with expertise in Python, Data Analytics, Graph Databases, and AWS, responsible for designing, building, and supporting scalable ...

Next Step Systems

Data Engineer, Python & ETL

Chicago, IL · On-site

$118K - $141K/yr

Data Engineer, Python & ETL, Chicago, IL A proprietary trading firm is seeking a Data Engineer ... tasks, data quality analysis, data modelling, monitoring, and automation. Qualifications ...

National Association of REALTORS

Data Analyst

Chicago, IL · Hybrid

$75K - $95K/yr

Develop and maintain Python notebooks using SQL, Spark, and related technologies for data analysis, exploration, and reporting * Create dashboards that effectively communicate insights to business ...

Next Step Systems

Python Software Engineer

Chicago, IL · On-site

Python Software Engineer, Chicago, IL A proprietary trading firm with three locations in Chicago ... tasks, data quality analysis, data modelling, monitoring, and automation. This position will be ...

Saicon Consultants Inc.

Data Analyst

Rosemont, IL · On-site

Data analysis tools like Excel and Python preferred. * Exposure to ETL tools, data warehouses, and APIs. * Data Skills: * Data profiling, quality assessment, and reconciliation break analysis. * Data ...

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Python Data Analysis Internship information

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

As of Aug 9, 2026, the average hourly pay for python data analysis internship in Libertyville, IL is $21.88, according to ZipRecruiter salary data. Most workers in this role earn between $16.83 and $23.85 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?

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 job categories do people searching Python Data Analysis Internship jobs in Libertyville, IL look for? The top searched job categories for Python Data Analysis Internship jobs in Libertyville, IL are:
What cities near Libertyville, IL are hiring for Python Data Analysis Internship jobs? Cities near Libertyville, IL with the most Python Data Analysis Internship job openings:
Python Data Analysis Internship jobs near you

Senior Software Engineer(Python)

Swift Hire LLC

Chicago, IL • On-site

$126K - $166K/yr

Contractor

Posted 4 days ago

Job description

Title - Senior Software Engineer(Python)

Senior Software Engineer with expertise in Python, Data Analytics, Graph Databases, and AWS, responsible for designing, building, and supporting scalable cloud-native backend services, APIs, and data-driven solutions.

Responsibilities: -

  • Design, build, and maintain backend services and APIs using Python (FastAPI, Flask, Django).
  • Model and query complex relationships using Graph Databases such as Neo4j, Amazon Neptune, or similar.
  • Architect, deploy, and operate cloud-native services on AWS (Lambda, EC2/ECS/EKS, API Gateway, S3, RDS/DynamoDB/Neptune, CloudWatch, IAM, etc.).
  • Contribute to system design discussions, architectural reviews, and technical decision-making.
  • Implement CI/CD pipelines, automation, observability (logging/metrics/tracing), and deployment best practices.
  • Write scalable, clean, well-tested, and maintainable code.
  • Collaborate closely with cross-functional teams including frontend, DevOps, and data/ML.
  • Troubleshoot production issues and optimize performance, reliability, and cost.
  • Mentor junior/mid-level engineers and promote engineering best practices.

Experience: -

  • 8+ Years

Location: -

  • Chicago, IL

 

Educational Qualifications: -

  • Engineering Degree – BE/ME/BTech/MTech/BSc/MSc.
  • Technical certification in multiple technologies is desirable.

 

Skills: -

Mandatory skills

  • Experience Strong expertise in Python backend development with hands-on experience in frameworks such as FastAPI, Flask, or Django for building scalable APIs and enterprise applications.
  • Practical experience working with Graph Databases such as Neo4j, Amazon Neptune, or similar technologies, including graph data modeling and querying using Cypher, Gremlin, or SPARQL.
  • Hands-on experience with AWS cloud services including compute, storage, networking, monitoring, identity, and database services such as Lambda, EC2, ECS/EKS, API Gateway, S3, RDS, DynamoDB, Neptune, CloudWatch, and IAM.
  • Strong understanding of RESTful API design, microservices architecture, distributed systems, and event-driven application development.
  • Experience working with both relational and NoSQL databases, including PostgreSQL and DynamoDB.
  • Hands-on experience with source control, CI/CD workflows, Docker containers, automated testing frameworks, and deployment best practices.
  • Strong debugging, performance optimization, troubleshooting, and system design capabilities.
  • Experience working on Data Analytics solutions and data-driven application development

 

Good to Have Skills

  • Experience with Go (Golang) for building microservices and backend tooling.
  • Understanding of .NET-based applications and backend architecture patterns.
  • Experience with Terraform and Infrastructure as Code for AWS deployments.
  • Hands-on exposure to Kubernetes (EKS), Helm, and container orchestration platforms.
  • Experience with messaging and streaming platforms such as Kafka, SQS/SNS, and Kinesis.
  • Knowledge of cloud security, networking concepts, and AWS best practices.