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Python Data Analyst Jobs in North Carolina (NOW HIRING)

Euclid Innovations

Python Data Engineer

Charlotte, NC · On-site

... with data science and analytics teams. Responsibilities : • Design, develop, and maintain ... using Python and related technologies. • Implement ETL processes to collect, cleanse, and ...

Judge Group, Inc.

Data Analyst

Raleigh, NC · On-site

$27 - $28/hr

Data Analytics / Data Engineer Contractor This role supports two major system overhaul projects and ... Build and maintain automation scripts using Python. * Utilize Databricks for data processing and ...

Polar IT Services

Data Analyst

Charlotte, NC · On-site +1

Data Analyst Location: Charlotte, NC Mode Of Work: Hybrid It's a W2 role * Develop analytics ... Write python scripts to develop ETL jobs Required Skills (top 3 non-negotiables): * Looker and ...

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All JobsPython Data Analyst JobsPython Data Analyst Jobs in North Carolina

Python Data Analyst information

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$30.9K

$75.1K

$123.6K

How much do python data analyst jobs pay per year?

As of Sep 9, 2026, the average yearly pay for python data analyst in North Carolina is $75,103.00, according to ZipRecruiter salary data. Most workers in this role earn between $56,800.00 and $88,200.00 per year, depending on experience, location, and employer.

What does a Python data analyst do?

A Python Data Analyst leverages the Python programming language to collect, process, and analyze large sets of data. They use tools and libraries like Pandas, NumPy, and Matplotlib to clean data, perform statistical analysis, and create visualizations that help organizations make data-driven decisions. Their role often involves extracting insights from complex datasets, automating data workflows, and communicating findings to stakeholders through reports or dashboards. Python Data Analysts play a crucial part in turning raw data into actionable business intelligence.

What does a Python data analyst do?

As a Python data analyst, you use the Python programming language to develop tools for data mining, analysis, and data visualization. You typically develop a script to meet the specific data needs of your client or employer. Then, you test your code and perform debugging duties before deploying it in a live environment. Some data analysts also have algorithm creation responsibilities. In this case, after creating and testing an algorithm, you use Python with your algorithm to interpret data. You also develop reports to show to your clients or employers, and you may code a web app or interface that clients can use to visualize data sets.

What are the key skills and qualifications needed to thrive as a Python data analyst, and why are they important?

To thrive as a Python Data Analyst, you need strong analytical skills, a solid grasp of statistics, and proficiency in Python programming, often supported by a degree in data science, mathematics, or a related field. Familiarity with data analysis libraries like pandas and NumPy, visualization tools such as Matplotlib or Seaborn, and experience with data querying languages like SQL are typically required. Attention to detail, critical thinking, and effective communication help you derive insights and present findings clearly to stakeholders. These skills and qualities are vital for transforming raw data into actionable business intelligence and supporting data-driven decision-making.

How do Python data analysts typically collaborate with other departments within an organization?

Python Data Analysts often work closely with teams such as marketing, finance, and product development to provide data-driven insights that inform business decisions. They regularly participate in cross-functional meetings to understand departmental objectives, gather requirements for data analysis, and present their findings in an accessible manner. Effective communication and the ability to translate technical results into actionable recommendations are essential, as analysts often act as a bridge between technical data and non-technical stakeholders.

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

AspectPython Data AnalystData Scientist
Required SkillsPython, SQL, data visualization, statistical analysisPython, R, machine learning, statistical modeling
Work EnvironmentBusiness analytics, reporting, data cleaningAdvanced modeling, predictive analytics, research
Industry UsageFinance, marketing, healthcare, retailTech, finance, research, AI development

While both roles require Python and data analysis skills, Data Scientists typically engage in more complex modeling and machine learning, whereas Python Data Analysts focus on data cleaning, visualization, and reporting to support business decisions.

Is Python good for data analysts?

Python is widely used by data analysts due to its simplicity, extensive libraries like pandas and NumPy, and strong community support. It enables efficient data manipulation, analysis, and visualization, making it a valuable skill for the role.
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Python Data Analyst jobs near you
Infographic showing various Python Data Analyst job openings in North Carolina as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 83% Full Time, 11% Part Time, and 4% Contract. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution, with an average salary of $75,103 per year, or $36.1 per hour.

Data Analyst / Product Analyst - Capital Markets

Lake Park, NC • On-site

Long Finch Technologies
IT Services • 51 - 200 employees
Learn more about Long Finch Technologiesexternal

Full-time

Posted 21 days ago

Job description

We are seeking an experienced Data Analyst / Product Analyst with 10+ years of experience in Capital Markets, financial services, or banking environments. The ideal candidate will have strong hands-on expertise in SQL, Python, data analysis, and business data analysis, combined with experience supporting complex, multi-business and multi-system initiatives.

Responsibilities:

  • Perform business and data analysis using SQL and Python to identify trends, patterns, data issues, and actionable insights.
  • Analyze complex Capital Markets data and business processes across multiple businesses and systems.
  • Gather, manage, and document business/functional requirements, including user stories, use cases, acceptance criteria, and test scripts.
  • Develop customer journey maps and analyze business processes to identify gaps and opportunities for improvement.
  • Support design and solution-related activities for complex, multi-business, multi-system initiatives.
  • Work closely with Product Owners, business stakeholders, developers, QA, and technology teams within an Agile/Scrum environment.
  • Support product lifecycle development, including requirements, design, testing, implementation, and post-production activities.
  • Use Jira to manage requirements, user stories, backlog items, defects, and project deliverables.

Qualifications Required:

  • 10+ years of experience in Data Analysis, Business Analysis, Product Analysis, or a related field.
  • Strong hands-on experience with SQL and Python.
  • Strong Capital Markets domain experience; Banking/Financial Services experience is preferred.
  • Excellent analytical, problem-solving, and business data analysis skills.
  • Experience with requirements management, user stories, use cases, test scripts, and customer journey mapping.
  • Strong experience working in Agile/Scrum environments and using Jira.
  • Experience supporting complex, multi-business and multi-system initiatives with strong stakeholder communication skills.

Preferred Qualifications:

  • Experience in Banking or Financial Services.

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