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Python Data Analyst Jobs in Portland, OR (NOW HIRING)

Senior Data Analyst

Beaverton, OR · On-site

$89K - $112K/yr

Senior Data Analyst- NIKE, Inc.- Beaverton, OR. Design, develop, and implement new decision support solutions that help the business leverage data to make informed decisions; assist the business

Big Data Laser Analyst Description - Job Summary We are seeking a highly analytical, business-oriented Data Analyst to support the Print Supplies business. In this role, you will translate consumer

Senior Data Analyst, BI & Analytics

Portland, OR · On-site

$91K - $115K/yr

Salary: About PayRange PayRange is a leading fintech and mobile commerce platform transforming the unattended retail industry through innovative payment and technology solutions. Our platform enables

Senior Data Analyst, BI & Analytics

Portland, OR · On-site

$91K - $115K/yr

About PayRange PayRange is a leading fintech and mobile commerce platform transforming the unattended retail industry through innovative payment and technology solutions. Our platform enables

We are looking for a Data Scientist to analyze large amounts of raw information to find patterns that will help improve our company. We will rely on you to build data products to extract valuable

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Showing results 1-20

Python Data Analyst information

See Portland, OR salary details

$36.1K

$87.6K

$144.2K

How much do python data analyst jobs pay per year?

As of Jun 20, 2026, the average yearly pay for python data analyst in Portland, OR is $87,640.00, according to ZipRecruiter salary data. Most workers in this role earn between $66,300.00 and $102,900.00 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.

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.

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.

Are Python coders still in demand?

Python data analysts are currently in high demand due to the language's versatility in data analysis, machine learning, and automation. Skills in libraries like Pandas, NumPy, and experience with data visualization tools increase employability across various industries.

Is 40 too old to become a data analyst?

Age is not a barrier to becoming a data analyst. Many professionals successfully transition into data analysis at various ages by acquiring skills in programming languages like Python or SQL, and gaining experience with data visualization tools. Employers value skills and experience over age, and continuous learning can help you stay competitive in the field.

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.

Is Python useful for data analysts?

Python is highly useful for data analysts as it offers powerful libraries like Pandas, NumPy, and Matplotlib for data manipulation, analysis, and visualization. It is widely used in the industry for automating tasks, building data pipelines, and performing statistical analysis, making it a valuable skill for the role.

Will AI replace data analysts?

AI is transforming the role of data analysts by automating routine tasks such as data cleaning and basic analysis, but it is unlikely to fully replace them. Data analysts are needed to interpret complex insights, make strategic decisions, and develop models that require domain expertise and critical thinking. Skills in programming, data visualization, and understanding AI tools remain valuable in this evolving field.
What are the most commonly searched types of Python Data Analyst jobs in Portland, OR? The most popular types of Python Data Analyst jobs in Portland, OR are:
What job categories do people searching Python Data Analyst jobs in Portland, OR look for? The top searched job categories for Python Data Analyst jobs in Portland, OR are:
What cities near Portland, OR are hiring for Python Data Analyst jobs? Cities near Portland, OR with the most Python Data Analyst job openings:

$90K - $114K/yr

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Job description

Job Description
Job Duties:
• Develop and support data solutions in support of Supply Chain Planning reporting and analytics requirements
• Engage with product owner, technology lead, report developers, product analysts, and business partners to understand capability requirements and develop data solutions based on product backlog priorities
Requirements
Skills / Qualifications:
• 5+ years of experience with data engineering with emphasis on data analytics and reporting
• Experience developing with scripting languages such as Shell and Python
• Strong experience developing with PySpark, preferably leveraging AWS EMR managed service
• Expert experience with SQL and Relational database engineering (Oracle, SQL Server, Teradata)- expert-level SQL abilities
• Experience with agile delivery methodologies- Scrum, SAFe, Extreme Programming
• Experience working with source-code management tools such as GitHub and Jenkins
• Ability to partner with business and technology team members, to understand business requirements and translate those into value-add technology solutions
Additional preferences are:
• Experience developing solutions in Snowflake
• Experience with workload automation tools such as Airflow, Autosys.
• Knowledge of building solutions with data visualization and reporting tools (Tableau, Cognos)
• Knowledge of Supply Chain Operations / Manufacturing business processes and objectives
Skill Set
Python, SQL, Data