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

... access to sensitive data through integrations, creating new risks most security tools miss ... Interface with Product and Engineering on root cause analysis, bug escalation, and permanent ...

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Python Data Analyst information

See Spokane, WA salary details

$34.4K

$83.6K

$137.5K

How much do python data analyst jobs pay per year?

As of Aug 6, 2026, the average yearly pay for python data analyst in Spokane, WA is $83,559.00, according to ZipRecruiter salary data. Most workers in this role earn between $63,200.00 and $98,100.00 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.

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 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.

What are 10 careers related to Python Data Analyst?

Careers related to a Python Data Analyst include Data Scientist, Business Intelligence Analyst, Data Engineer, Data Architect, Quantitative Analyst, Machine Learning Engineer, Data Consultant, Data Operations Manager, Data Warehouse Developer, and Research Analyst. These roles often require skills in programming, data visualization, and statistical analysis, and may involve working with tools like SQL, Tableau, or cloud platforms.

What is the salary of a Python Data Analyst?

The salary of a Python Data Analyst typically ranges from $60,000 to $100,000 annually, depending on experience, location, and industry. Professionals with strong skills in Python, data visualization, and statistical analysis tend to earn higher salaries, especially in tech hubs or large organizations.
What are the most commonly searched types of Python Data Analyst jobs in Spokane, WA? The most popular types of Python Data Analyst jobs in Spokane, WA are:
What are popular job titles related to Python Data Analyst jobs in Spokane, WA? For Python Data Analyst jobs in Spokane, WA, the most frequently searched job titles are:
What job categories do people searching Python Data Analyst jobs in Spokane, WA look for? The top searched job categories for Python Data Analyst jobs in Spokane, WA are:
What cities near Spokane, WA are hiring for Python Data Analyst jobs? Cities near Spokane, WA with the most Python Data Analyst job openings:
Infographic showing various Python Data Analyst job openings in Spokane, WA as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 17% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $83,559 per year, or $40.2 per hour.

Forward Deployed Engineer I/II, AI Enablement

Washington Trust Bank

Spokane, WA • On-site

Full-time

Medical, Life, Retirement

Posted 14 days ago


Job description

The Forward Deployed Engineer, AI Enablement partners with business areas across the Bank to identify, design, build, document, and improve AI-enabled workflows and capabilities that make it easy to Sell, Service, and Scale the company. This role helps translate business needs into practical solutions by combining business process understanding, data literacy, AI fluency, stakeholder communication, and lightweight technical implementation. The Forward Deployed Engineer works with business users, process owners, technology, data, security, risk, and governance partners to develop safe, useful, and reusable AI-enabled tools, templates, workflows, documentation, and service patterns. This position requires curiosity, critical thinking, creativity, strong follow-through, and comfort operating in work that may not be fully defined at the start.

Essential Functions:

  • Embeds with business teams and process owners to understand how work moves end to end across people, processes, systems, data, decisions, controls, handoffs, and exception paths.
  • Identifies high-value opportunities to reduce cognitive, context, coordination, execution, quality, or design burden.
  • Determines whether AI, deterministic automation, data capability, reporting, process redesign, or human judgment is the appropriate response.
  • Designs future-state workflows with clear ownership, human and AI responsibilities, review points, exception handling, data boundaries, system interactions, and control requirements.
  • Designs, builds, and validates working AI-enabled solutions that combine agents, approved data, APIs, automation, reporting, workflow components, and human review into cohesive business capabilities.
  • Develops agent instructions, system prompts, tool-use patterns, structured outputs, context and retrieval approaches, evaluation criteria, error handling, and escalation paths appropriate to the use case.
  • Uses programming, scripting, agentic development workflows, APIs, approved platforms, and automation tools to build, inspect, test, debug, and refine solutions.
  • Builds small, testable versions; validates them with domain experts and users; and iterates based on workflow fit, output quality, reliability, usability, adoption, and business value.
  • Advances successful prototypes toward operational use by defining production-readiness requirements, runbooks, monitoring expectations, service ownership, permissions, support paths, change requirements, and control points with appropriate partners.
  • Documents assumptions, decisions, limitations, risks, dependencies, evaluation results, support requirements, and handoff information so capabilities can be reviewed, maintained, supported, and reused.
  • Measures outcomes such as reduced cycle time, fewer handoffs, less rework, improved consistency, stronger decision context, increased operating capacity, adoption, governance confidence, and reuse.
  • Converts successful local solutions into reusable agents, modules, templates, data or context assets, playbooks, evaluation patterns, and service models that accelerate future work.
  • Identifies when an AI-enabled approach is inappropriate and recommends deterministic process, data, reporting, automation, or human-owned alternatives.
  • Escalates data, security, privacy, risk, compliance, governance, production, integration, or supportability concerns early and works with the appropriate owners to resolve or document them.

Qualifications:

  • Demonstrated ability to understand complex business processes, identify high-value improvement opportunities, and translate them into practical technology-enabled solutions.
  • Experience designing, building, testing, and operationalizing AI-enabled workflows, agents, automations, applications, reporting, or decision-support capabilities.
  • Working knowledge of agentic AI concepts, including instructions, tool use, structured outputs, contextual grounding, retrieval, human review, exception handling, orchestration, and evaluation.
  • Proficiency with at least one modern programming or scripting language, such as Python, C#, JavaScript, or TypeScript, with the ability to learn and apply new technologies quickly.
  • Experience using agentic and command-line development workflows—including tools such as GitHub Copilot and Codex-style coding agents—to plan, generate, inspect, test, debug, and refine solutions.
  • Ability to direct coding agents through clear goals, context, constraints, acceptance criteria, and iterative review while maintaining human accountability for the resulting solution.
  • Experience integrating systems and data through APIs, connectors, automation platforms, relational databases, analytical platforms, or event-driven patterns.
  • Ability to build small, testable solutions, validate them directly with users, and iteratively improve reliability, usability, workflow fit, and measurable business value.
  • Strong data fluency, including experience with structured and unstructured data, data models, reporting, analytics, and the context required to ground AI solutions.
  • Experience within Microsoft’s enterprise technology ecosystem, which may include Microsoft Fabric, Azure AI Foundry, Microsoft 365 Copilot, Copilot Studio, GitHub Copilot, Power BI, Power Platform, Azure, and related services.
  • Understanding of production-readiness considerations, including permissions, security, monitoring, error handling, documentation, support ownership, change management, and operational controls.
  • Ability to work across business, operations, technology, data, security, risk, compliance, and governance teams in a regulated enterprise environment. Banking or financial-services experience is preferred.
  • Strong written, verbal, documentation, and facilitation skills, including the ability to create clear technical and operational materials, embed with business teams, learn unfamiliar domains quickly, explain technical concepts clearly, and navigate ambiguity.
  • Sound judgment in determining when AI is appropriate and when deterministic processes, traditional automation, reporting, data, or human-owned solutions would be more effective.
  • A builder mindset characterized by curiosity, adaptability, ownership, practical problem-solving, accountability for measurable outcomes, and the ability to convert successful solutions into reusable components and patterns.
  • Demonstrated self-motivation, initiative, attention to detail, and organizational ability; works effectively both independently and collaboratively.
  • Ability to prioritize multiple assignments, manage interruptions, and maintain a high level of service in a deadline-driven environment.
  • Ability to work additional hours as required by operational and production workloads.

Compensation:

Forward Deployed Engineer I - $87,093 - $130,697
Forward Deployed Engineer II - $99,830 - $149,745

The compensation range represents the low and high end of the base compensation range for this position located in Spokane, WA. Actual compensation will vary and may be above or below the range based on various factors including but not limited to location, experience, and performance. This position is eligible to participate in an applicable incentive plan.

What Our Culture Can Offer You:

Our benefit philosophy is to provide you with a comprehensive package to secure your overall wellness and help you become and remain a fulfilled and productive employee. Our benefits include Health, Financial, Retirement and Work/Life Benefits. We are proud to share an overview of our benefits HERE as part of your total compensation.

Washington Trust Bank celebrates diversity in the workplace and actively recruits talent to help reflect the unique communities where we live and work. We are proud to be an equal opportunity employer and prohibit discrimination or harassment based on race, religion, sex, gender identity, sexual orientation, national origin, age, pregnancy, disability, genetic information and any other protected characteristics outline by state, federal and local laws. We believe strength comes from the diverse backgrounds and experiences of our team, and we are dedicated to fostering a supportive and inclusive work environment.