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Data Science Major Jobs in Seattle, WA (NOW HIRING)

TikTok

Data Science Manager - TikTok Ads

Seattle, WA · On-site

$242K - $401K/yr

... on major cross-functional measurements, testing, and modeling efforts 6. Partner with Data ... SQL) 5. Experience building data science models (Regression, Decision Trees, K-Means, etc ...

Docugami

Data Science PhD Intern

Kirkland, WA

We're now looking for AI, NLP, Machine Learning, Data Science, and Math PhD Interns to work ... We are looking for exceptional researchers to work with our luminary science advisers on major ...

Docugami

Data Science PhD Intern

Kirkland, WA · On-site

We're now looking for AI, NLP, Machine Learning, Data Science, and Math PhD Interns to work ... We are looking for exceptional researchers to work with our luminary science advisers on major ...

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Data Science Major information

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

To thrive as a Data Science Major, you need a solid understanding of mathematics, statistics, and programming languages such as Python or R, typically backed by coursework or a related degree. Familiarity with data analysis tools, machine learning libraries, and platforms like SQL, TensorFlow, or Jupyter Notebook is also important. Critical thinking, effective communication, and problem-solving skills help you interpret data insights and collaborate on projects. These competencies enable you to extract meaningful information from data, drive decision-making, and succeed in a data-driven environment.

What is a Data Science major?

A Data Science major is an academic program that focuses on teaching students how to collect, analyze, and interpret large sets of data to solve real-world problems. It combines coursework in statistics, computer science, mathematics, and domain-specific knowledge to prepare graduates for roles in various industries such as technology, healthcare, finance, and more. Students learn programming languages like Python or R, machine learning techniques, and data visualization skills. The major often includes hands-on projects and internships to provide practical experience in analyzing and extracting insights from data.

What types of projects or problems do Data Science majors typically work on during internships or entry-level roles?

Data Science majors in internships or entry-level positions often collaborate on projects involving data cleaning, exploratory data analysis, and building predictive models. They might work with real-world datasets to identify trends, automate reporting, or support business decision-making with data-driven insights. These roles typically require teamwork with software engineers, business analysts, and domain experts, offering valuable opportunities to apply classroom knowledge to practical challenges and to develop skills in popular tools like Python, R, and SQL.

What jobs can you do with data science?

Data science majors can pursue roles such as data analyst, data scientist, machine learning engineer, business intelligence analyst, and data engineer. These positions typically require skills in programming, statistical analysis, and data visualization tools like Python, R, SQL, and Tableau, often with relevant certifications or advanced degrees.

Is data science a good major?

Data science is a strong major for those interested in careers involving data analysis, machine learning, and statistical modeling. It prepares students with skills in programming, data manipulation, and tools like Python and R, which are highly valued in many industries. Graduates often find opportunities in technology, finance, healthcare, and consulting sectors.

What kind of jobs can I get with a data science degree?

A data science degree prepares individuals for roles such as data scientist, data analyst, machine learning engineer, and business intelligence analyst. These jobs typically require skills in programming languages like Python or R, statistical analysis, and data visualization tools, often within technology, finance, healthcare, or marketing industries.

What is the difference between Data Science Major vs Data Analyst?

AspectData Science MajorData Analyst
Required CredentialsDegree in Data Science, Computer Science, or related fieldsDegree in Statistics, Mathematics, or related fields
Work EnvironmentResearch, development, and complex data modelingData interpretation, reporting, and visualization
Industry UsageTech companies, finance, healthcare, academiaBusiness, marketing, finance, healthcare
Common Search/ComparisonData Science Major vs Data Analyst

While both roles involve working with data, a Data Science Major typically prepares individuals for complex data modeling, machine learning, and research tasks. In contrast, a Data Analyst focuses on interpreting data, creating reports, and visualizations to support business decisions. The roles often overlap, but the Data Science Major emphasizes advanced analytics and programming skills, whereas Data Analysts concentrate on data interpretation and communication.

What are the careers in data science?

Careers in data science include roles such as data scientist, data analyst, machine learning engineer, and data engineer. These positions involve analyzing large datasets, developing predictive models, and using tools like Python, R, and SQL to support decision-making across various industries.
What job categories do people searching Data Science Major jobs in Seattle, WA look for? The top searched job categories for Data Science Major jobs in Seattle, WA are:
What cities near Seattle, WA are hiring for Data Science Major jobs? Cities near Seattle, WA with the most Data Science Major job openings:
Data Science Major jobs near you
Infographic showing various Data Science Major job openings in Seattle, WA as of July 2026, with employment types broken down into 1% As Needed, 82% Full Time, 12% Part Time, 1% Temporary, and 4% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution.
Principal, Data Science & Analytics

Principal, Data Science & Analytics

Microsoft

Redmond, WA • On-site

Full-time

Posted 20 days ago

Microsoft rating

8.5

Company rating: 8.5 out of 10

Based on 131 frontline employees who took The Breakroom Quiz

78th of 245 rated software companies

Job description

Overview
Microsoft AI (MAI) builds an integrated consumer AI ecosystem across search, browsing, and content, focused on delivering trustworthy, scalable experiences with durable user and business value. The MAI Ecosystem Data Science Team owns MAI-wide metrics, shared measurement systems, and experimentation frameworks to enable consistent, high-confidence decisions and optimize MAI-level outcomes.
We are seeking a Principal, Data Science & Analytics for ecosystem data science to own cross product measurement strategy, partner across product and business teams, and uphold a high bar for metric quality, statistical rigor, and data driven leadership.
We are looking for high-energy Data Scientist, creative modeling geeks who are willing to work in a dynamic environment to solve real life day to day problems, leveraging data science techniques. You will enjoy and be successful in this role if you are curious and willing to challenge the status quo and come up with data driven solutions to ambiguous problems.
Microsoft's mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
Starting January 26, 2026, Microsoft AI (MAI) employees who live within a 50- mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week. This expectation is subject to local law and may vary by jurisdiction.
Responsibilities
As a Principal, Data Science and Analytics in the team, your major responsibilities include:
  • Leadership: Mentor data scientists and align work with MAI ecosystem goals, driving technical excellence, innovation, and cross-team collaboration.
  • Data Strategy & Execution: Develop ecosystem data strategies for marketplace and system performance, including standardized data collection, analysis, reporting, and interpretation; validate analytical approaches and results.
  • Advanced Analytics & Measurement: Apply machine learning, statistical modeling, data mining, and experimentation to large datasets; define and deliver metrics that accurately measure user and business value across products and marketplace components.
  • Experimental Design & Implementation: Design and execute experiments across user and demand dimensions; translate strategy into clear, actionable, and measurable plans, sharing progress and results with stakeholders.
  • Collaboration: Partner closely with product, program management, engineering, and business teams to integrate data science solutions into shared platforms and marketplace operations.
  • Performance Optimization: Identify cross-team opportunities for product and process improvement; implement data-driven solutions to improve efficiency, reliability, and user experience.
  • Influence & Decision-Making: Engage stakeholders with clear, compelling, and actionable insights; make independent decisions for the team and handle complex tradeoffs to drive product and service improvements.
  • Technical & Operational Leadership: Develop and standardize processes for data acquisition, quality, and operationalizing ML models; provide expert review of analysis and modeling; lead adoption of new tools and technologies to improve availability, reliability, efficiency, and performance.
  • Standards & Trusted Advisory: Establish and uphold standards, policies, and best practices for high-quality, efficient, and extensible code; influence business, customer, and solution strategy with a strong customer focus; act as a trusted advisor across the ecosystem.

Qualifications
Required Qualifications:
  • Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
    • OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 7+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
    • OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 10+ years data science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
    • OR equivalent experience.

Preferred Qualifications:
  • Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 8+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
    • OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 10+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
    • OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 12+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
    • OR equivalent experience.

#MicrosoftAI
Data Science IC5 - The typical base pay range for this role across the U.S. is USD $142,800 - $274,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000 - $304,200 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

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About Microsoft

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Our infrastructure is comprised of a large global portfolio of more than 100 datacenters and 1 million servers. Our foundation is built upon and managed by a team of subject matter experts working to support services for more than 1 billion customers and 20 million businesses in over 90 countries worldwide. With environmental sustainability and optimization at the forefront of our datacenter design and operations, we continue to grow and evolve as we meet the ever-changing business demands that hold Microsoft as a world-class cloud provider.

Industry

Computer and computer peripheral equipment and software wholesalers

Company size

10,000+ Employees

Headquarters location

Redmond, WA, US

Year founded

1975

Social media

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