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Ai Data Analytics Jobs in Renton, WA (NOW HIRING)

McKinstry

Senior Data Analyst, People Analytics

Seattle, WA · On-site

$97K - $123K/yr

Support the data foundation for AI-enabled analytics by ensuring people data is well-defined, governed, secure, and appropriately integrated with enterprise data sources. * Monitor and resolve data ...

Deloitte

Lead Generative AI Data Engineer III

Seattle, WA

$116K - $153K/yr

Our offerings help clients innovate, enhance, and operate their data, AI, and analytics capabilities, ensuring they can mature and scale effectively with organizational intelligence programs and ...

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How much do ai data analytics jobs pay per hour?

As of Aug 22, 2026, the average hourly pay for ai data analytics in Renton, WA is $61.83, according to ZipRecruiter salary data. Most workers in this role earn between $49.66 and $70.05 per hour, depending on experience, location, and employer.

What is AI data analytics?

AI Data Analytics refers to the use of artificial intelligence technologies to analyze and interpret large volumes of data. By leveraging machine learning algorithms, natural language processing, and other AI methods, professionals in this field can uncover patterns, make predictions, and drive data-driven decision-making. AI Data Analytics is widely used across industries to optimize operations, improve customer experiences, and gain competitive insights. The role typically involves working with big data platforms, developing models, and communicating findings to stakeholders.

What skills and qualifications are needed to thrive as an AI data analyst?

To thrive as an AI Data Analyst, you need a strong background in statistics, data analysis, and machine learning, typically supported by a degree in computer science, mathematics, or a related field. Proficiency with tools such as Python, R, SQL, and data visualization platforms like Tableau, along with knowledge of AI frameworks such as TensorFlow or PyTorch, is essential. Strong problem-solving skills, attention to detail, and effective communication help you interpret complex data and present actionable insights to stakeholders. These skills are crucial for driving data-driven decision-making and maximizing the impact of AI initiatives within organizations.

How does an AI data analytics professional typically collaborate with cross-functional teams within an organization?

AI Data Analytics professionals frequently work alongside departments such as marketing, operations, IT, and product development to interpret complex datasets and provide actionable insights. Collaboration often involves translating business needs into data-driven solutions, communicating findings in accessible terms, and ensuring that analytics projects align with organizational goals. Effective teamwork and clear communication are crucial, as analytics professionals must bridge the gap between technical data analysis and practical business application.

What is the difference between Ai Data Analytics vs Data Scientist?

AspectAi Data AnalyticsData Scientist
Required CredentialsBachelor's in Data Science, Computer Science, or related fields; certifications in AI and data analyticsBachelor's or higher in Data Science, Statistics, Computer Science; advanced degrees preferred
Work EnvironmentTech companies, finance, healthcare; focus on AI-driven data analysisResearch labs, tech firms, finance; focus on data modeling and insights
Employer & Industry UsageUsed in industries leveraging AI for predictive analytics and automationUsed across industries for data modeling, predictive analytics, and research

Ai Data Analytics professionals focus on applying AI techniques to analyze data and develop automated solutions, while Data Scientists build models and interpret data to generate insights. Both roles require strong analytical skills and familiarity with data tools, but Ai Data Analytics emphasizes AI implementation, whereas Data Scientists focus on statistical modeling and research.

Is data analysis a good career with AI?

A career in AI Data Analytics is considered promising due to the increasing demand for data-driven decision making and AI integration across industries. Professionals in this field need strong skills in data manipulation, statistical analysis, and tools like Python or R. The role offers growth opportunities, competitive salaries, and the chance to work on innovative technologies.

What does an AI data analyst do?

An AI data analyst collects, processes, and analyzes large datasets to extract insights that inform business decisions. They use tools like Python, R, and machine learning algorithms to identify patterns and trends, often working closely with data engineers and data scientists to develop predictive models and automate data workflows.

What are popular job titles related to Ai Data Analytics jobs in Renton, WA?

For Ai Data Analytics jobs in Renton, WA, the most frequently searched job titles are:

What job categories do people searching Ai Data Analytics jobs in Renton, WA look for?

The top searched job categories for Ai Data Analytics jobs in Renton, WA are:

What cities near Renton, WA are hiring for Ai Data Analytics jobs?

Cities near Renton, WA with the most Ai Data Analytics job openings:

Ai Data Analytics jobs near you
Infographic showing various Ai Data Analytics job openings in Renton, WA as of June 2026, with employment types broken down into 82% Full Time, and 18% Part Time. Highlights an 75% Physical, 3% Hybrid, and 22% Remote job distribution, with an average salary of $128,088 per year, or $61.6 per hour.

Principal Product Manager - AI Data Quality

F5, Inc.

Seattle, WA • On-site

$156K - $235K/yr

Full-time

Re-posted yesterday

Job description

At F5, we strive to bring a better digital world to life. Our teams empower organizations across the globe to create, secure, and run applications that enhance how we experience our evolving digital world. We are passionate about cybersecurity, from protecting consumers from fraud to enabling companies to focus on innovation.
Everything we do centers around people. That means we obsess over how to make the lives of our customers, and their customers, better. And it means we prioritize a diverse F5 community where each individual can thrive.
The Mission
We are building an AI-native enterprise, and high-fidelity data is the substrate.
We are looking for a technically fluent Product Manager to architect and scale an AI-Ready Data Quality Platform built on Databricks and Unity Catalog.
This is not a traditional MDM or stewardship role.
You will define and ship the platform capabilities that make our AI Data Fabric trustworthy, observable, and production-grade - from real-time anomaly detection to CI/CD-native schema enforcement to automated data contract validation.
If you think of data quality as code, treat governance as infrastructure, and believe AI systems are only as good as the data feeding them - this role is for you.
What You'll Own
Build the AI-Ready Data Quality Platform
  • Define and ship native data quality capabilities inside Databricks Lakehouse

  • Productize policies and controls within Unity Catalog (lineage, access, schema enforcement)

  • Embed data contracts and validation logic directly into pipelines

  • Partner with data engineering to integrate dbt-based transformation layers into quality frameworks

  • Drive metadata, lineage, and semantic standardization as first-class platform features

Operationalize Data Quality in the AI Data Fabric
  • Design real-time anomaly detection systems (statistical + ML-driven)

  • Build upstream schema validation into CI/CD workflows (shift-left quality)

  • Define SLOs/SLAs for data products

  • Enable automated drift detection for training and inference datasets

  • Implement observability across streaming and batch architectures

You will treat data quality like SRE treats uptime.
Drive Data Ownership as a Product Discipline
  • Establish a data product ownership model across service teams

  • Define what "production-grade data" means for AI use cases

  • Build self-service tooling for teams to monitor and certify their data

  • Incentivize measurable quality accountability at the domain level

This role transforms culture by building the platform that enforces it.
AI + Governance Convergence
  • Define how governed datasets become AI-ready assets

  • Enable traceability from raw source → curated feature sets → model inputs

  • Align catalog metadata with AI feature stores and inference pipelines

  • Partner with ML teams to support model reproducibility and dataset versioning

What You Bring
  • 5+ years in Product Management for Data Platforms, Analytics, or AI Infrastructure

  • Deep working knowledge of:

  • Databricks Lakehouse architecture

  • Unity Catalog governance constructs

  • dbt transformation workflows

  • CI/CD patterns for data pipelines

  • Data observability and monitoring patterns

  • Strong SQL fluency and comfort reading Python/Scala data pipeline code

  • Experience defining data contracts and schema evolution strategies

  • Understanding of streaming frameworks (Kafka, Spark Structured Streaming, etc.)

  • Experience supporting AI/ML workloads in production environments

Bonus:
  • Experience with modern data observability platforms (Monte Carlo, Bigeye, etc.)

  • Familiarity with feature stores and model lifecycle tooling

  • Knowledge of domain-oriented data mesh architectures

How We Measure Success
  • % of AI datasets certified as "production-grade"

  • Reduction in downstream model failures due to data issues

  • Automated anomaly detection coverage across critical pipelines

  • Adoption of data ownership model across service domains

  • CI/CD-integrated data validation coverage

Why This Role Matters
AI systems amplify whatever data they are fed.
This role ensures:
  • We trust our data.

  • Our models are reproducible.

  • Governance is automated.

  • Quality is engineered, not inspected.

You won't be managing spreadsheets of bad records.
You will be building the infrastructure that makes AI reliable at scale.
#LI-JB1
The Job Description is intended to be a general representation of the responsibilities and requirements of the job. However, the description may not be all-inclusive, and responsibilities and requirements are subject to change.
The annual base pay for this position is: $156,800.00 - $235,200.00
F5 maintains broad salary ranges for its roles in order to account for variations in knowledge, skills, experience, geographic locations, and market conditions, as well as to reflect F5's differing products, industries, and lines of business. The pay range referenced is as of the time of the job posting and is subject to change.
You may also be offered incentive compensation, bonus, restricted stock units, and benefits. More details about F5's benefits can be found at the following link: https://www.f5.com/company/careers/benefits. F5 reserves the right to change or terminate any benefit plan without notice.
Please note that F5 only contacts candidates through F5 email address (ending with @f5.com) or auto email notification from Workday (ending with f5.com or @myworkday.com)
Equal Employment Opportunity
It is the policy of F5 to provide equal employment opportunities to all employees and employment applicants without regard to unlawful considerations of race, religion, color, national origin, sex, sexual orientation, gender identity or expression, age, sensory, physical, or mental disability, marital status, veteran or military status, genetic information, or any other classification protected by applicable local, state, or federal laws. This policy applies to all aspects of employment, including, but not limited to, hiring, job assignment, compensation, promotion, benefits, training, discipline, and termination. F5 offers a variety of reasonable accommodations for candidates. Requesting an accommodation is completely voluntary. F5 will assess the need for accommodations in the application process separately from those that may be needed to perform the job. Request by contacting accommodations@f5.com.

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