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Data Science Jobs in Seattle, WA (NOW HIRING)

Boeing

Data Scientist (Data Science)

Everett, WA · On-site

$173K - $234K/yr

Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Physics, Engineering, or a related quantitative field. * Strong proficiency in Python or R, and advanced SQL for data ...

Boeing

Data Scientist (Data Science)

Everett, WA · On-site

$173K - $234K/yr

Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Physics, Engineering, or a related quantitative field. * Strong proficiency in Python or R, and advanced SQL for data ...

Boeing

Data Scientist (Data Science)

Everett, WA · On-site

$173K - $234K/yr

Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Physics, Engineering, or a related quantitative field. * Strong proficiency in Python or R, and advanced SQL for data ...

iSpot

Data Science Intern

Bellevue, WA · Hybrid

$35/hr

The Research Data Science team builds innovative solutions for iSpot's audience measures, attribution and lift analytics, creative testing, and artificial intelligence implementations. After ...

iSpot

Data Science Intern

Bellevue, WA · Hybrid

$35/hr

The Research Data Science team builds innovative solutions for iSpot's audience measures, attribution and lift analytics, creative testing, and artificial intelligence implementations. After ...

Microsoft

Data Science Strategy Lead

Redmond, WA · On-site

Set the long term Data Science strategy, defining where to intentionally invest, differentiate, and deprioritize to maximize sustained business value. • Develop Multi Year Vision and Roadmap:

iSpot

Data Science Intern

Bellevue, WA · On-site

$35/hr

The Research Data Science team builds innovative solutions for iSpot's audience measures, attribution and lift analytics, creative testing, and artificial intelligence implementations. After ...

Walmart

(USA) Senior Manager, Data Science

Bellevue, WA · On-site

Drive Data Science Innovation to protect the integrity of the Marketplace by applying advanced statistical methods, machine learning, and AI techniques to identify and mitigate fraud and performance ...

Boeing

Data Science & Analytics Manager

Everett, WA · On-site

$183K - $224K/yr

Data Science & Analytics Manager Company: The Boeing Company Summary: Boeing Commercial Airplanes is looking for a Data Science & Analytics Managers to join the Supply Chain Functional Excellence ...

Docusign

Product Data Science Intern

Seattle, WA · On-site

As a Data Scientist Intern, you'll dig into the data to uncover insights, identify opportunities for product improvements and new product development, define product metrics with goals, design ...

DocuSign

Product Data Science Intern

Seattle, WA · On-site +1

As a Data Scientist Intern, you'll dig into the data to uncover insights, identify opportunities for product improvements and new product development, define product metrics with goals, design ...

Chewy

Associate Director, Data Science

Bellevue, WA

In this role, you will lead a high-performing team of Data Scientists and Machine Learning Engineers while driving the vision, strategy, and execution of AI and machine learning capabilities across ...

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All JobsData Science JobsData Science Jobs in Seattle, WA

Data Science information

See Seattle, WA salary details

$42.7K

$139.7K

$223.6K

How much do data science jobs pay per year?

As of Jun 13, 2026, the average yearly pay for data science in Seattle, WA is $139,691.00, according to ZipRecruiter salary data. Most workers in this role earn between $112,100.00 and $154,800.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Data Scientist, and why are they important?

To thrive as a Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, usually supported by a degree in a quantitative field. Familiarity with machine learning libraries (like scikit-learn or TensorFlow), big data tools (such as Hadoop or Spark), and data visualization platforms is typically required. Critical thinking, problem-solving, and effective communication are vital soft skills for translating complex data insights into actionable business strategies. These skills and qualities are essential for extracting value from data, driving informed decisions, and effectively collaborating with multidisciplinary teams.

Is 40 too late for data science?

Data science is a field open to individuals of all ages, and many professionals transition into it later in their careers. Success often depends on acquiring relevant skills such as programming, statistics, and machine learning, which can be learned through online courses, bootcamps, or degrees regardless of age.

What are some common challenges faced by data scientists when working with real-world datasets?

Data scientists often encounter challenges such as missing or inconsistent data, unstructured formats, and noisy information in real-world datasets. Cleaning and preprocessing data to ensure its quality can be time-consuming but is critical for building accurate models. Additionally, data scientists may work closely with domain experts and other team members to better understand the data's context and ensure their analyses align with business objectives. Overcoming these challenges requires strong problem-solving skills and effective collaboration within cross-functional teams.

Is AI replacing data scientists?

AI is transforming the role of data scientists by automating routine tasks such as data cleaning and basic analysis, but it does not replace the need for skilled professionals to interpret complex data, develop models, and make strategic decisions. Data scientists with expertise in programming, statistical analysis, and machine learning remain essential for designing and deploying AI solutions effectively.

What is data science?

Data science is an interdisciplinary field that uses scientific methods, algorithms, and systems to extract insights and knowledge from structured and unstructured data. It combines skills from statistics, computer science, and domain expertise to analyze and interpret complex data sets. Data scientists work with large amounts of data to identify patterns, make predictions, and help organizations make data-driven decisions.

What is the difference between Data Science vs Data Analyst?

AspectData ScienceData Analyst
Required skillsStatistics, programming (Python, R), machine learningData visualization, SQL, basic statistics
Work environmentDeveloping models, predictive analytics, researchReporting, data cleaning, descriptive analysis
Tools usedPython, R, Jupyter, TensorFlowExcel, SQL, Tableau, Power BI
Industry usageTech, finance, healthcare, e-commerceRetail, marketing, finance, healthcare

Data Science and Data Analyst roles often overlap but differ mainly in scope. Data Scientists focus on building predictive models and advanced analytics, requiring programming and machine learning skills. Data Analysts primarily handle data cleaning, reporting, and visualization. Both roles are essential in data-driven industries, but Data Science is more technical and research-oriented, while Data Analysis emphasizes interpreting data for business insights.

What jobs are there in data science?

Data science offers a variety of roles including Data Scientist, Data Analyst, Machine Learning Engineer, Data Engineer, and Business Intelligence Analyst. These positions typically require skills in programming, statistics, and data visualization tools, and may involve working with large datasets, predictive modeling, and data-driven decision making.

What Does a Data Scientist Do?

As a Data Scientist, you are qualified to work in such diverse fields as research and development, politics, advertising and marketing, technology, healthcare, government, and higher education as well as multiple others. In general, your duties and responsibilities will be to compile and analyze relevant statistics and turn those numbers into algorithms that reveal insights that can be used by other researchers in their areas of study. Data Science can reveal things like consumer buying habits or the likelihood of success for a course of action. Other duties might vary, depending on your unique field of specialty. Related areas in which a Data Scientist might wish to focus include work as a Data Analyst, Machine Learning Engineer, and Project Manager.

What jobs does a data scientist do?

A data scientist analyzes large datasets to extract insights, build predictive models, and support decision-making. They use programming languages like Python or R, employ statistical techniques, and often work with machine learning algorithms to solve complex problems across various industries.
More about Data Science jobs
What are the most commonly searched types of Data Science jobs in Seattle, WA? The most popular types of Data Science jobs in Seattle, WA are:
What are popular job titles related to Data Science jobs in Seattle, WA? For Data Science jobs in Seattle, WA, the most frequently searched job titles are:
What job categories do people searching Data Science jobs in Seattle, WA look for? The top searched job categories for Data Science jobs in Seattle, WA are:
What cities near Seattle, WA are hiring for Data Science jobs? Cities near Seattle, WA with the most Data Science job openings:
Data Science jobs near you

Data Science Specialist

ANICCA DATA SCIENCE SOLUTIONS LLC

Bellevue, WA • On-site

$87K - $101K/yr

Full-time

Posted 17 days ago

Job description

Role Summary
We are looking for an experienced Data Professional to support Azure-based data platform, analytics, reporting, and advanced analytics and science work. The role requires hands-on experience in data engineering, data analysis, business intelligence, and Python-based analytics using Microsoft Azure technologies.
Key Responsibilities
* Design, build, and maintain data pipelines using Azure Data Factory, Azure Data Lake Gen2, Synapse, Fabric, and Databricks.
* Ingest, transform, and validate data from multiple business systems, APIs, databases, and files.
* Develop and maintain data models, source-to-target mappings, business rules, and data quality checks.
* Perform data profiling, reconciliation, gap analysis, and root-cause analysis.
* Write complex SQL, Python, PySpark, and KQL queries for data processing and analysis.
* Build and support Power BI dashboards, reports, semantic models, KPIs, and analytical datasets.
* Apply statistical analysis, forecasting, anomaly detection, and basic machine learning techniques where needed.
* Support Dev/UAT/Prod deployments, CI/CD, documentation, testing, and stakeholder sign-off.
* Ensure data security, governance, RBAC, access control, and performance best practices.
Required Skills
* 5+ years of experience in data engineering, data analytics, BI, or data science.
* Strong hands-on experience with Azure data services.
* Strong skills in SQL, Python, PySpark, Power BI, and data modeling.
* Experience with ADF, ADLS Gen2, Synapse/Fabric, Databricks, dbt, or Airbyte.
* Ability to translate business requirements into technical specifications, data models, reports, and analytics solutions.
* Experience with data validation, documentation, UAT support, and stakeholder communication.
* Knowledge of Azure DevOps, Git, CI/CD, and Agile delivery is preferred.
Qualifications
Bachelor’s or Master’s degree in Computer Science, Data Science, Information Technology, Engineering, Statistics, or a related field.