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Entry Level Data Scientist Jobs in Renton, WA (NOW HIRING)

... GenAI Data Scientist - Manager, you will play a pivotal role in transforming raw data into ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

Currently, we are looking for entry-level software programmers, Java Full stack developers, Python ... We want Data Science/Machine learning/Data Analyst and Java Full stack candidates REQUIRED SKILLS ...

... entry-level technical assistance on various environmental issues. * Work on multiple projects ... Bachelor's Degree in Environmental Science, Geology, Chemistry, Natural Resources Management ...

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Entry Level Data Scientist information

See Renton, WA salary details

$51.7K

$185.6K

$273.9K

How much do entry level data scientist jobs pay per year?

As of Jun 18, 2026, the average yearly pay for entry level data scientist in Renton, WA is $185,616.00, according to ZipRecruiter salary data. Most workers in this role earn between $150,200.00 and $191,200.00 per year, depending on experience, location, and employer.

What Does an Entry-Level Data Scientist Do?

An entry-level data scientist works to examine, interpret, and collect large sets of data. In this role, your responsibilities include extracting and processing information to find patterns and trends, using technology to analyze data, and creating a machine-learning algorithm or predictive model for data analysis. Other duties include proposing strategies and solutions based on the information you derived from a data set, using ensemble modeling to combine models, automating processes to collect data, discovering valuable data sources, and using data visualization techniques to present information. You often collaborate with product development and engineering teams.

What does an Entry Level Data Scientist do?

An Entry Level Data Scientist helps organizations analyze and interpret large sets of data to solve business problems. They typically assist with data cleaning, exploratory data analysis, and building simple machine learning models under the supervision of more experienced data scientists. Their work often involves using programming languages like Python or R, and tools such as SQL and data visualization software. Entry level data scientists also collaborate with other team members to communicate findings and support data-driven decision-making.

What are some typical challenges faced by entry level data scientists in their first year on the job?

Entry level data scientists often encounter challenges such as working with messy or incomplete datasets, adapting to unfamiliar data tools and company-specific processes, and translating business problems into actionable data analyses. They may also find it challenging to communicate technical findings to non-technical stakeholders and to prioritize projects in a fast-paced environment. Building strong relationships with colleagues in engineering, business, and analytics teams is key to overcoming these challenges and accelerating learning.

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

To thrive as an Entry Level Data Scientist, you need a solid foundation in statistics, programming (typically Python or R), and data analysis, often supported by a degree in a quantitative field such as mathematics, computer science, or engineering. Familiarity with tools like SQL, Jupyter Notebooks, and machine learning libraries (e.g., scikit-learn, TensorFlow) is commonly expected. Strong problem-solving skills, curiosity, and effective communication are essential soft skills for interpreting data and presenting findings to stakeholders. These abilities enable you to extract actionable insights from data, support business decisions, and contribute value to data-driven organizations.

What is the difference between Entry Level Data Scientist vs Data Analyst?

AspectEntry Level Data ScientistData Analyst
Required CredentialsBachelor's in CS, Statistics, or related field; some knowledge of programming and machine learningBachelor's in Business, Statistics, or related field; strong Excel, SQL, and visualization skills
Work EnvironmentCollaborates with data science teams, uses programming languages like Python or R, focuses on predictive modelingWorks with business teams, uses SQL, Excel, and BI tools, focuses on reporting and data visualization
Employer & Industry UsageTech companies, finance, healthcare, startupsRetail, marketing, finance, healthcare, government

Entry Level Data Scientists and Data Analysts often share foundational skills like SQL and data visualization. However, data scientists typically focus on building predictive models and machine learning algorithms, requiring programming knowledge, while data analysts concentrate on interpreting data through reports and dashboards. Both roles are essential in data-driven organizations but differ in technical depth and project scope.

What are the most commonly searched types of Data Scientist jobs in Renton, WA? The most popular types of Data Scientist jobs in Renton, WA are:
What are popular job titles related to Entry Level Data Scientist jobs in Renton, WA? For Entry Level Data Scientist jobs in Renton, WA, the most frequently searched job titles are:
What job categories do people searching Entry Level Data Scientist jobs in Renton, WA look for? The top searched job categories for Entry Level Data Scientist jobs in Renton, WA are:
What cities near Renton, WA are hiring for Entry Level Data Scientist jobs? Cities near Renton, WA with the most Entry Level Data Scientist job openings:
Entry level Java spring boot developer/ data scientist

Entry level Java spring boot developer/ data scientist

SynergisticIT

Seattle, WA

$59 - $80.75/hr

Other

Posted 4 days ago


Job description

CS/IT Graduates or About to be Grads. Get Hired by following a Process!
Graduating with a CS degree is impressive - but it's not enough anymore. Employers want hands-on experience, real projects, and interview-ready candidates.
Getting hired in tech isn't just about knowing how to code - it's about proving you can deliver value from day one. Despite layoffs and market shifts, the tech industry still needs skilled developers. The challenge is proving you're ready to contribute. A CS degree gives you a foundation, but employers want more - they want proof you can apply your knowledge in real-world scenarios.
If you just graduated (or you're about to) and the job search is already feeling confusing, you're not imagining it. A degree proves you can learn-but employers hire for job readiness: projects that look like real work, current tech stacks, interview confidence, and the ability to contribute on day one. That's why many new grads send hundreds of applications and still hear nothing back. It's not because you're "not smart enough." It's because most entry-level pipelines are crowded, and hiring teams filter heavily for candidates who look production-ready.
We are actively considering candidates for entry-level software engineering and data roles, especially Java full stack, Java/Python development, DevOps automation, data analytics, data engineering, data science, and ML/AI-full-time opportunities aligned to client needs. Our core emphasis remains Java/Full Stack/DevOps and Data/Analytics/Engineering/ML.
SynergisticIT focuses on two high-demand lanes: Java / Full Stack / DevOps and Data (Data Analyst, Data Engineer, Data Scientist) + ML/AI-so you don't graduate with scattered skills, you graduate with an employable stack.
SynergisticIT since 2010, has helped candidates land full-time roles at major organizations ( including Google, Apple, PayPal, Visa, Western Union, Wells Fargo, Client, Banking, Wayfair, Client, Client, and more) with offers commonly in the $95k-$154k range depending on role and skill depth. For a new grad, the bigger message isn't the number-it's that results require a structured pathway, not random applications.
Here's a realistic way to think about your advantage as a fresh graduate: you're early enough to build the right foundation before bad habits set in. If you master fundamentals-coding, debugging, data structures, system thinking-and then layer modern tools on top (frameworks, cloud, CI/CD, analytics stacks), you become the kind of "entry-level" candidate who actually feels like a safe hire.
What roles are companies hiring for right now? A typical market demand pattern is clear: organizations still need entry-level software programmers, Java full stack developers, Python/Java developers, DevOps-focused engineers, and on the data side data analysts, BI analysts, data engineers, data scientists, and machine learning engineers. The strongest candidates aren't "tool collectors"-they're people who can show end-to-end capability: build an API, connect a database, deploy a service, analyze data, explain results, and handle interviews calmly.
Why fresh grads get stuck-
Fresh grads often struggle for four predictable reasons:
  1. Resume doesn't match job keywords (ATS filters you out).
  2. Projects look like school assignments (not production-aligned).
  3. Interview skills are undertrained (DSA, system design, SQL, behavioral).
  4. No structured pipeline (random applying without feedback loops).
A job-placement-first approach addresses these systematically: build the right portfolio, practice the right interview questions, align your tech stack to roles, and keep improving until the market says "yes."
Who this path fits best
If you're a recent graduate, you'll likely fit if you match any of these:
  • New grads in CS, Engineering, Math, or Statistics with limited job experience
  • Students finishing Bachelor's or Master's programs who need a real hiring plan
  • Candidates who apply consistently but don't get callbacks
  • Candidates who reach interviews but struggle to close
  • International students on F-1/OPT who need a job plan for STEM extension/H-1B timing
  • Graduates with strong academics but thin practical experience
SynergisticIT helps STEM extension and work authorization pathways, and for candidates who need long-term stability, support related to H-1B and green card processes as part of employer-side realities.
If you're tired of guessing, stop treating your job search like a lottery. Treat it like a project with milestones: skills → portfolio → interview readiness → targeted applications → scheduled interviews → offer.
If you want to explore, here are the key links:
  • Event videos (OCW, JavaOne, Gartner):
  • USA Today feature
  • Contact & get a roadmap: https://www.synergisticit.com/contact-us/

Please read our blogs
Why do Tech Companies not Hire recent Computer Science Graduates | SynergisticIT
What Recruiters Look for in Junior Developers | SynergisticIT
Software engineering or Data Science as a career?
Bottom line for fresh grads: Your degree is the starting line, not the finish line. If you want to get hired faster, you don't need "more random courses." You need a guided, job-focused path and the right people around you. In tech, it's not just what you learn-it's how you learn and who you build with that decides how far you go.
Please note: Resume databases are shared with clients and interested clients will reach out directly if they find a qualified candidate for their req.
Resume submissions may be shared with our JOPP team database also. Please unsubscribe if contacted or if you don't want to be contacted please don't submit your resume