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Freelance Python Data Analysis Jobs in Michigan (NOW HIRING)

GCP Data Engineer with Python

Dearborn, MI ยท On-site

$105K - $126K/yr

Role: GCP Data Engineer with Python Location: Dearborn, MI (4 days a week onsite) Job Type ... The engineer will collaborate with existing team members, including Software Analysts and Scrum ...

Utilize statistical techniques and data analysis tools (i.e., Python, R, SQL) to gather, clean, analyze, and provide recommendations regarding large datasets from various sources, identifying trends ...

Use data modeling tools, data analysis tools, advanced programming languages like R, Python, SQL, etc. * Identify and implement avenues to optimize and enhance data analysis, interpretation and ...

Python proficiency, including experience with libraries and tools used for data analysis and automation. * Experience with Power BI or similar visualization tools, including dashboard design and KPI ...

Data Analyst

Warren, MI ยท On-site

Python proficiency, including experience with libraries and tools used for data analysis and automation. * Experience with Power BI or similar visualization tools, including dashboard design and KPI ...

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Freelance Python Data Analysis information

What is freelance Python data analysis?

Freelance Python data analysis involves using the Python programming language to analyze and interpret data for clients on a project or contract basis. Freelancers in this field typically work with datasets to extract insights, visualize results, and help businesses make data-driven decisions. They often use libraries such as pandas, NumPy, and matplotlib, and may work across industries like finance, marketing, healthcare, and technology. Freelancers enjoy flexibility in choosing their projects and clients, and often work remotely.

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

To thrive as a Freelance Python Data Analyst, you need strong analytical skills, proficiency in Python programming, and a solid understanding of statistics and data manipulation, often backed by a relevant degree or proven portfolio. Experience with tools such as Pandas, NumPy, Jupyter Notebooks, and data visualization libraries like Matplotlib or Seaborn is typically required. Excellent problem-solving abilities, communication skills, and the ability to manage projects independently distinguish top performers in this role. These skills enable analysts to deliver actionable insights, meet client expectations, and maintain a successful freelance business.

What are some common challenges freelance Python data analysts face when working with clients remotely?

Freelance Python data analysts often encounter challenges such as clarifying project requirements, managing client expectations about deliverables, and ensuring timely communication across different time zones. Working remotely can also mean troubleshooting data access or security issues, especially if clients have strict data privacy policies. Building trust through regular updates and transparent reporting is key to successful collaborations in this role.
What are the most commonly searched types of Python Data Analysis jobs in Michigan? The most popular types of Python Data Analysis jobs in Michigan are:
What are popular job titles related to Freelance Python Data Analysis jobs in Michigan? For Freelance Python Data Analysis jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Freelance Python Data Analysis jobs in Michigan look for? The top searched job categories for Freelance Python Data Analysis jobs in Michigan are:
What cities in Michigan are hiring for Freelance Python Data Analysis jobs? Cities in Michigan with the most Freelance Python Data Analysis job openings:
Infographic showing various Freelance Python Data Analysis job openings in Michigan as of July 2026, with employment types broken down into 82% Full Time, 15% Part Time, and 3% Contract. Highlights an 83% Physical, 4% Hybrid, and 13% Remote job distribution.

GCP Data Engineer with Python

Saransh Inc

Dearborn, MI โ€ข On-site

$105K - $126K/yr

Contractor

Posted 27 days ago


Job description

Role:ย GCP Data Engineer with Python
Location:ย Dearborn, MI (4 days a week onsite)
Job Type: Contract
ย 
Experience: Overall 8 to 12 years

Job Summary:
  • The Data Engineer will be responsible for supporting the Credit Global Securitization (GS) teamโ€™s upskilling initiative by contributing to data engineering efforts across cloud and traditional platforms.
  • This role is intended to accelerate development and delivery.
  • The engineer will work closely with cross-functional teams to build, optimize, and maintain data pipelines and workflows using GCP, Python, and ETL tools.

Required Technical Skills:
  • Minimum 3+ years of hands-on experience with Google Cloud Platform (GCP), specifically using Astronomer/Composer for orchestration.
  • Strong proficiency in Python for data engineering and automation.
  • Experience with RDBMS technologies such as DB2 and Teradata.
  • Exposure to Big Data ecosystems and distributed data processing.

Nice to have Technical Skills:
  • Prior experience with ETL tools like DataStage or Informatica.

Responsibilities:
  • The Data Engineer will play a key role in the developing and maintaining scalable data pipelines and workflows.
  • The engineer will work with GCP tools like Astronomer/Composer and leverage Python for automation and transformation tasks.
  • The role involves integrating data from RDBMS platforms such as DB2 and Teradata, and supporting ETL processes using tools like DataStage or Informatica.
  • The engineer will collaborate with existing team members, including Software Analysts and Scrum Masters, and will be expected to contribute to knowledge sharing and process improvement.
    ย 
Specifically:
  • Develop and implement solutions using GCP, Python, Big Data technologies to enhance data analysis capabilities.
  • Collaborate with cross-functional teams to design and optimize data models in Teradata and DB2 environments.
  • Utilize Python for scripting and automation to streamline geospatial data processing tasks.
  • Integrate and manage data workflows using Cloud Composer to ensure efficient data pipeline operations.
  • Leverage GCP Cloud to deploy scalable applications and services.