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Python Data Analyst Jobs in Vancouver, WA (NOW HIRING)

Nike

Senior Data Analyst

Beaverton, OR · On-site

$89K - $112K/yr

Senior Data Analyst- NIKE, Inc.- Beaverton, OR. Design, develop, and implement new decision support ... Python programming with libraries such as Spark and Pandas • Familiarity with REST API ...

Mattson Technology

Data Analyst Engineer

Hillsboro, OR · On-site

Proficiency in data analysis tools (e.g., Excel, SQL, Python, or similar) * Experience with data visualization tools (e.g., Power BI, Tableau) preferred * Strong analytical, problem-solving, and ...

HP

Supplies North America Business Analyst

Vancouver, WA · On-site

$83K - $127K/yr

... Python, or similar). Knowledge & Skills * Data Analysis * Data Science * AI-Enabled Analytics ... Statistical Analysis * Business Analytics * Business Intelligence * Advanced Excel * Excel Modeling

Hp

Supplies North America Business Analyst

Vancouver, WA

$83K - $127K/yr

... Python, or similar). Knowledge & Skills * Data Analysis * Data Science * AI-Enabled Analytics ... Statistical Analysis * Business Analytics * Business Intelligence * Advanced Excel * Excel Modeling

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All JobsPython Data Analyst JobsPython Data Analyst Jobs in Vancouver, WA

Python Data Analyst information

See Vancouver, WA salary details

$35.6K

$86.5K

$142.4K

How much do python data analyst jobs pay per year?

As of Jul 7, 2026, the average yearly pay for python data analyst in Vancouver, WA is $86,521.00, according to ZipRecruiter salary data. Most workers in this role earn between $65,400.00 and $101,600.00 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.

Will AI replace a data analyst?

AI tools can automate routine data processing and analysis tasks, but the role of a data analyst involves interpreting insights, understanding business context, and communicating findings, which require human judgment. Data analysts who develop skills in programming, data visualization, and machine learning can adapt to new technologies and continue to add value in data-driven decision-making.

Is 40 too old to become a data analyst?

Age is not a barrier to becoming a data analyst; many professionals transition into the field later in life. Success depends on acquiring relevant skills such as SQL, Python, and data visualization, along with practical experience and certifications. Employers value diverse backgrounds and experience, making it possible to start a data analyst career at any age.

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 a high paying job?

Python Data Analysts are generally well-compensated due to their technical skills in programming, data manipulation, and analysis. Salaries vary based on experience, location, and industry, but proficiency in Python often leads to higher earning potential compared to many other entry-level roles in data analysis. Certifications and knowledge of related tools like SQL or machine learning can further increase salary prospects.

Is Python useful for data analysts?

Python is highly useful for data analysts because 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.
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Python Data Analyst jobs near you

Sr Data Analyst

BizTek People, Inc. | APA International Placement Consultants

Beaverton, OR • On-site

$90K - $114K/yr

Contractor

Posted 18 days ago

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

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