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

AI Data Engineer

Redmond, WA ยท On-site

$128K - $154K/yr

... assist them with data access. * Identify and analyse multi-structured data or metadata from a ... Bachelor's Degree in Computer Science, Software Engineering, Computer Engineering, or related field ...

... assist users in creating new documents more efficiently and consistently, and can automatically ... Docugami is looking for Machine Learning, Data Science and Math PhD researchers to work alongside ...

... assistant, Alexa for shopping. Successful candidate will demonstrate strong attention to detail ... In this role, you will mentor and set the bar for data science, economics, and engineering partners ...

... assistant, Alexa for shopping. Successful candidate will demonstrate strong attention to detail ... In this role, you will mentor and set the bar for data science, economics, and engineering partners ...

In this role, you will collaborate with software engineering, data science, and product management ... * Assist in owning existing processes running in production, optimizing complex code through ...

In this role, you will collaborate with software engineering, data science, and product management ... * Assist in owning existing processes running in production, optimizing complex code through ...

In this role, you will collaborate with software engineering, data science, and product management ... * Assist in owning existing processes running in production, optimizing complex code through ...

In this role, you will collaborate with software engineering, data science, and product management ... * Assist in owning existing processes running in production, optimizing complex code through ...

While this is an engineering-first role, you will also work with the Data Science team to assist in their application of statistical modeling and machine learning to help turn raw data into ...

As a technical leader, the person will assist with setting the technical direction of the practice ... Bachelor's degree in computer science or related field * 12 years of industry experience, with 4 ...

Showing results 21-40

Data Science Assistant information

What is a data science assistant?

Data Science Assistants are professionals who support data scientists and analytics teams by handling tasks such as data collection, data cleaning, preparing datasets, conducting preliminary analyses, and creating visualizations. They often work with large datasets, assist in maintaining data integrity, and help automate routine processes. Their role allows data scientists to focus on more complex modeling and analytical work, making the overall workflow more efficient. Data Science Assistants typically have a foundational understanding of statistics, programming (such as Python or R), and data management tools.

What are the key skills and qualifications needed to thrive as a data science assistant?

To thrive as a Data Science Assistant, you need a solid understanding of statistics, data analysis, and programming (often with a background in mathematics, computer science, or a related field). Familiarity with tools like Python or R, data visualization software, and experience with databases or spreadsheet systems are typically required. Attention to detail, strong problem-solving abilities, and effective communication set outstanding candidates apart. These skills are crucial for supporting data-driven decision-making and ensuring accurate, actionable insights for organizations.

How does a data science assistant typically collaborate with data scientists and other team members on projects?

As a Data Science Assistant, you will frequently support data scientists by preparing datasets, conducting preliminary data analysis, and creating visualizations. You will often work closely with analysts, engineers, and subject matter experts to gather requirements and ensure data is cleaned and formatted appropriately. Collaboration is a key part of the role, as you may participate in team meetings, share findings, and help with documentation to keep projects running smoothly. This supportive environment provides an excellent opportunity to learn from experienced professionals and gain exposure to the full data science workflow.

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

AspectData Science AssistantData Analyst
Required CredentialsBachelor's in Data Science, Statistics, or related fieldBachelor's in Statistics, Mathematics, or related field
Work EnvironmentTech companies, research labs, data-driven departmentsBusiness, finance, marketing, healthcare sectors
Employer & Industry UsageUsed in data science teams for supporting models and analysisUsed across industries for interpreting data and generating reports

While both roles involve working with data, a Data Science Assistant typically supports data science projects, focusing on data preparation and model testing. A Data Analyst primarily interprets data to generate insights and reports. The roles overlap in skills and work environments but differ in their core responsibilities and focus areas.

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 Assistant jobs in Seattle, WA? For Data Science Assistant jobs in Seattle, WA, the most frequently searched job titles are:
Infographic showing various Data Science Assistant job openings in Seattle, WA as of August 2026, with employment types broken down into 6% Internship, 79% Full Time, 9% Part Time, 3% Temporary, and 3% Contract. Highlights an 94% In-person, and 6% Remote job distribution.

AI Data Engineer

1 point system

Redmond, WA โ€ข On-site

$128K - $154K/yr

Contractor

Re-posted 4 days ago


Job description

Candidate Requirements

Disqualifiers: Repetitive, overly long, or generic or keyword heavy resumes that lack context on impact or outcomes (ex, just listing tools/tech without explaining business value) will likely be disqualified

Best vs. Average: The ideal resume would contain resumes that clearly demonstrate how their work drives business impact (ex. improved performance, enabled decision making, supported marketing or product outcomes) and show strong critical thinking and problem solving in how they present their experience.

Top 3 Must-Have HARD Skills & years of experience for each:   

  1. Python 4-5 years
  2. Data Modeling 3 years
  3. Marketing 2 years

Responsibilities

  • Build subject matter expertise of our business and data domains to collaborate with data consumers and stakeholders to understand their information needs and assist them with data access.
  • Identify and analyse multi-structured data or metadata from a variety of sources to select and document the most effective and accurate data which fulfils the analytics requirements.
  • Design data models, architect dataflows, and develop abstractions to deliver scalable solutions for analytics and machine learning ensuring they can evolve with changing needs.
  • Leverage modern data engineering practices and frameworks with an object-oriented approach to architect, build, and maintain automated data pipelines which transform data into clean, enriched, and accurate information.
  • Advance our infrastructure by developing frameworks, reusable components and new capabilities to achieve our mission.
  • Enable the Franchise performance marketing strategy through the development of relevant and robust data products.

 

Required Qualifications

  • Bachelor's Degree in Computer Science, Software Engineering, Computer Engineering, or related field AND 4+ years’ experience in analytics engineering, data engineering, data science, data analyst, or related software development work
  • Master's Degree in Computer Science, Software Engineering, Computer Engineering, or related field AND 3+ years’ experience in analytics engineering, data engineering, data science, data analyst, or related software development work
  • OR equivalent experience.
  • 2+ years working as an Analytics Engineer or Data Engineer with regular business collaboration or equivalent on large enterprise systems.
  • Experience building, maintaining and optimizing enterprise scale data pipelines handling logs and event streaming data on Cloud Data Platforms using modern tools like Spark, and airflow; Azure preferred.
  • Proficiency with SQL; Advanced skills with Python for data transformation and automation

 

Preferred Qualifications

  • Critical thinker and problem solver who brings a creative and open mindset.
  • A proven track record building and optimizing analytic solutions and data products which deliver significant business impact.
  • Data analysis and exploration skills to identify, select and prepare data for analytics.
  • Business acumen to address business challenges through analytics engineering.
  • Experience building, maintaining and optimizing enterprise scale data pipelines handling logs and event streaming data on Cloud Data Platforms using modern tools like Spark, and airflow; Azure preferred.
  • Working knowledge of DevOps and DataOps.