1

Computer Science Jobs in Kitsap County, WA (NOW HIRING)

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience * 3+ years of experience developing and designing Computer Vision and ...

Masters or PhD degree in Computer Science, Computer Vision, Robotics, or a related technical field * Publication track record at conferences such as SIGGRAPH, CVPR, NeurIPS, ECCV, ICCV, ISMAR, ICML ...

Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured ...

Showing results 41-60

Computer Science information

See Kitsap County, WA salary details

$59.8K

$88K

$103.8K

How much do computer science jobs pay per year?

As of Sep 7, 2026, the average yearly pay for computer science in Kitsap County, WA is $88,023.00, according to ZipRecruiter salary data. Most workers in this role earn between $82,100.00 and $99,000.00 per year, depending on experience, location, and employer.

What is computer science?

Computer science is the study of computers, computational systems, and how they process information. It covers a wide range of topics, including programming, algorithms, data structures, artificial intelligence, and software engineering. Computer scientists design and analyze software and hardware to solve problems and improve technology. The field is essential in many industries, from finance and healthcare to entertainment and research.

What are computer science jobs?

The computer science field provides a wide range of opportunities for technically talented individuals. Depending on your skills and interests, you can find computer science jobs as a software developer, hardware engineer, database administrator, computer systems analyst, network architect, information security analyst, or web developer. You need an analytical mind and strong technical skills to perform your job duties, which may be to develop, maintain, and troubleshoot computer systems, applications, or networks. Your responsibilities in a computer science job are often directly related to the business goals and outcomes of your employer.

What are the key skills and qualifications needed to thrive in a computer science role, and why are they important?

To thrive in a Computer Science role, you need strong programming skills, problem-solving abilities, and a degree in computer science or a related field. Familiarity with languages like Python, Java, C++, version control systems such as Git, and software development methodologies is often required. Analytical thinking, attention to detail, and effective teamwork are valuable soft skills that set candidates apart. These skills ensure you can design efficient solutions, collaborate on complex projects, and adapt to rapidly evolving technologies.

What are some common challenges computer science professionals face when working on collaborative software projects?

Computer science professionals often encounter challenges such as coordinating with team members across different disciplines, managing version control in shared codebases, and ensuring clear communication of technical concepts to non-technical stakeholders. Navigating conflicting priorities and integrating diverse components can also be demanding, especially in agile environments with tight deadlines. Strong collaboration skills, openness to feedback, and familiarity with team tools like Git and project management platforms can help address these challenges effectively.

What is the difference between Computer Science vs Software Developer?

AspectComputer ScienceSoftware Developer
Required CredentialsBachelor's or higher in CS or related fieldBachelor's in CS, Software Engineering, or related field often preferred
Work EnvironmentResearch labs, academia, tech companies, startupsTech companies, software firms, freelance projects
Industry UsageAcademic research, algorithm development, theoretical workBuilding, coding, testing software applications
Common Search/ComparisonFocuses on theoretical foundations and algorithmsFocuses on practical software creation and deployment

Computer Science and Software Developer roles often overlap, but Computer Science emphasizes theoretical foundations, algorithms, and research, while Software Developers focus on designing, coding, and maintaining software applications. Both roles require programming skills, but their primary focus and work environments differ.

Are computer science majors still in demand?

Computer science majors are currently in high demand due to the growth of technology, software development, cybersecurity, and data analysis fields. Employers seek candidates with programming skills, knowledge of algorithms, and experience with tools like Python, Java, and cloud platforms, making it a strong career choice with good job prospects.

What are careers in computer science?

Careers in computer science include roles such as software developer, systems analyst, cybersecurity analyst, data scientist, and network administrator. These jobs typically require strong programming skills, knowledge of algorithms, and familiarity with tools like programming languages, databases, and operating systems.

What can you do with a computer science degree?

A computer science degree prepares individuals for a variety of roles such as software developer, systems analyst, cybersecurity analyst, data scientist, and network administrator. It provides skills in programming, algorithms, and systems design, often requiring knowledge of programming languages, databases, and problem-solving. Graduates can work in technology companies, finance, healthcare, or government agencies, often with opportunities for certification and ongoing learning.

What jobs can I do with computer science?

A degree in computer science opens opportunities for roles such as software developer, systems analyst, cybersecurity analyst, data scientist, and network administrator. These jobs typically require programming skills, knowledge of algorithms, and familiarity with tools like databases and operating systems.

What are the most commonly searched types of Computer Science jobs in Kitsap County, WA?

The most popular types of Computer Science jobs in Kitsap County, WA are:

What cities near Kitsap County, WA are hiring for Computer Science jobs?

Cities near Kitsap County, WA with the most Computer Science job openings:

Infographic showing various Computer Science job openings in Kitsap County, WA as of August 2026, with employment types broken down into 50% Full Time, and 50% Part Time. Highlights an 100% In-person job distribution, with an average salary of $88,023 per year, or $42.3 per hour.

Senior Data Scientist - Media Data Science & Analytics

Microsoft

Redmond, WA • On-site

Full-time

Re-posted 4 days ago


Microsoft rating

8.6

Company rating: 8.6 out of 10

Based on 134 frontline employees who took The Breakroom Quiz

69th of 247 rated software companies


Job description

Overview
We're building a Frontier Marketing organization where the Media Data Science & Analytics team leads the way in transforming how Microsoft measures, analyzes, and optimizes media investments. Our team blends advanced analytics, experimentation, and AI-powered insights to drive smarter decision-making and measurable business outcomes across paid media and owned digital properties.
We operate with agility, prioritize outcomes over activity, and embrace rapid learning loops to unlock deeper audience understanding, maximize campaign impact, and accelerate innovation in media strategy.
To support this transformation, we are seeking a Senior Data Scientist to help us measure the incremental impact of advertising spend and use that to help our media planning partners optimize media campaigns.
Marketing data science is inherently challenging: data is often observational, incomplete, biased, or limited in scale, and outcomes unfold over time across complex systems. The successful candidate will be someone who can apply rigorous causal methods, exercise sound statistical judgment, and translate uncertainty into actionable insights that inform high-stakes investment decisions.
Responsibilities
Causal Measurement & Business Impact
  • Design and apply causal inference approaches (e.g., quasi-experimental methods, incrementality testing, observational analysis) to estimate the true impact of media investments in settings where randomized experiments may be limited or infeasible.
  • Evaluate the effectiveness of marketing strategies while explicitly accounting for data limitations, confounding, selection bias, and uncertainty.
  • Translate complex causal findings into clear, decision-oriented narratives for senior marketing and business stakeholders.

Modeling, Statistics & Analysis
  • Apply advanced statistical techniques and machine learning where appropriate, with a bias toward interpretability and causal validity over purely predictive performance.
  • Balance methodological rigor with pragmatism, selecting approaches that are fit for purpose given the data and business context.
  • Write high-quality analytical code (Python, SQL) to support reproducible research, exploratory analysis, and ongoing measurement efforts.
  • Identify opportunities to improve measurement approaches, challenge existing assumptions, and introduce best practices grounded in both academic research and industry experience.

Data Understanding & Stewardship
  • Prepare, validate, and analyze complex marketing datasets, identifying data quality issues, structural changes, and limitations that materially affect inference.
  • Communicate data risks, constraints, and implications proactively to senior partners, ensuring conclusions are appropriately scoped and caveated.
  • Uphold high standards for data ethics, privacy, and responsible use, with careful attention to how data is collected, modeled, and interpreted.

What Success Looks Like
  • Media investment decisions are better informed by clear, credible causal insights rather than surface-level correlations.
  • Stakeholders understand not only what the data suggests, but how confident we are and why.
  • Analytical recommendations appropriately reflect data constraints and uncertainty, earning trust through transparency and rigor.
  • The team consistently applies causal thinking to difficult, ambiguous marketing problems, even when the data is imperfect.

Qualifications
Required/Minimum Qualifications
  • Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) 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 3+ 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 5+ 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 3+ 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 6+ 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 8+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR equivalent experience.
  • 5+ years' experience building ML models.
  • 5+ years' experience writing SQL to analyze data.
  • 5+ years' experience writing code in Python.
  • 3+ years' communicating complex technical concepts to non-technical partner teams.
  • 1+ years' experience performing causal inference
  • 1+ years' experience with media / marketing data science

Data Science IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 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 $160,200 - $261,000 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.

What Microsoft employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Microsoft logo

About Microsoft

Sourced by ZipRecruiter

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