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Data Science Assistant Jobs in Oregon (NOW HIRING)

OR ยท On-site

Apply a range of data science techniques and tools combined with subject matter expertise to solve ... AI assistants to deliver higher-quality work at pace What You'll Bring * 10+ years of data ...

AI and Data Science Engineer III

Portland, OR ยท On-site +1

$121K - $145K/yr

AI and Data Science Engineer III Position Summary Our Deloitte Human Capital team transforms ... knowledge assistants, summarization, and policy question-and-answer solutions using secure ...

OR ยท On-site

ABOUT THIS POSITION The Data Science focus specializes in extracting insights and solving complex ... * Assist in the development and implementation of statistical models, machine learning algorithms ...

OR ยท On-site

ABOUT THIS POSITION The Data Science focus specializes in extracting insights and solving complex ... * Assist in the development and implementation of statistical models, machine learning algorithms ...

OR ยท On-site

Data Science Analyst II ----- This position is responsible for proactively identifying ... * Assist with, prepare, and/or deliver presentations to community groups, regulatory agencies ...

OR ยท On-site

The team uses data science and quantitative methods to identify meaningful risks, align with ... problems. * Assist in exploring new data sources, research, and models under the direction of ...

... * Assist on research development projects and data science project plans for clients and internal initiatives * Strive to support team excellence by documenting processes and evangelizing new ...

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Data Science Assistant information

What are Data Science Assistants?

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, and why are they important?

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 Oregon? The most popular types of Data Science jobs in Oregon are:
What are popular job titles related to Data Science Assistant jobs in Oregon? For Data Science Assistant jobs in Oregon, the most frequently searched job titles are:
What job categories do people searching Data Science Assistant jobs in Oregon look for? The top searched job categories for Data Science Assistant jobs in Oregon are:
What cities in Oregon are hiring for Data Science Assistant jobs? Cities in Oregon with the most Data Science Assistant job openings:
Infographic showing various Data Science Assistant job openings in Oregon as of June 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, 1% Temporary, 1% Contract, and 1% Nights. Highlights an 98% Physical, 1% Hybrid, and 1% Remote job distribution.

Principal Data Scientist

Robots and Pencils

OR โ€ข On-site

Other

Posted 6 days ago


Job description

Robots & Pencils is an applied AI engineering firm building the next frontier of business architecture. We design and ship AI co-workers that integrate into enterprise operations and deliver measurable results for our clients.ย We're all in on AWS, combining deep UX capability with senior engineering talent to get AI into production fast and keep it there.ย 
We've earned the trust of leaders across Consumer Products and Retail, Education, Energy, Financial Services, Healthcare, and Manufacturing and more, and earned a reputation as the nimble alternative to traditional global systems integrators. Founded in 2009, with delivery centers in Canada, the United States, Eastern Europe, and Latin America, we are smaller, faster, and more senior by design. Our teams average 15+ years of experience. We move fast, sweat the details, and build things that actually ship.ย 

Position Overviewย 

We're looking for a Principal Data Scientist to join a multi-disciplinary team focused on designing and implementing scalable and reliable approaches to support or automate decision making throughout the business. This role is ideal for an experienced data scientist who can apply a range of data science techniques and tools combined with subject matter expertise to solve difficult business problems and cases in which the solution approach is unclear.

In this role, you will acquire data by building the necessary SQL / ETL queries and import processes through various company specific interfaces for accessing S3, RedShift, and Spark storage systems. You'll build relationships with stakeholders and counterparts, analyze data for trends and input validity, and implement models that comply with evaluations of computational demands, accuracy, and reliability. ย 

Why This Role Mattersย 

At Robots & Pencils, we design AI systems forย a humanย world. Our name says it all. Robots and pencilsย meansย engineering paired with creativity, because every agent we shipย has toย work for real people in real workflows. That balance is baked into how we operate.ย 
Every role here contributes directly to that mission. Here, you shape how AI systems integrate into enterprise operations, how teams move at real velocity, and how products create measurable impact for clients and the people they serve. We ship production-ready AI in 30 toย 45 days. That pace demands people who take ownership, lead with craft, and care deeply about what they put their name on.ย 

Whatย You'llย Doย 

Craft & Deliveryย 

  • Design and implement scalable and reliable approaches to support or automate decision making throughout the business
  • Apply a range of data science techniques and tools combined with subject matter expertise to solve difficult business problems and cases in which the solution approach is unclear
  • Acquire data by building the necessary SQL / ETL queries and import processes through various company specific interfaces for accessing S3, RedShift, and Spark storage systems
  • Analyze data for trends and input validity by inspecting univariate distributions, exploring bivariate relationships, constructing appropriate transformations, and tracking down the source and meaning of anomalies
  • Build models using statistical modeling, mathematical modeling, econometric modeling, network modeling, social network modeling, natural language processing, machine learning algorithms, genetic algorithms, and neural networks
  • Validate models against alternative approaches, expected and observed outcomes, and other business defined key performance indicators
  • Implement models that comply with evaluations of the computational demands, accuracy, and reliability of the relevant ETL processes at various stages of production
  • Implement and deploy state of the art machine learning algorithms under Gen AI, build prototypes, troubleshoot customer issues, and explore new solutionsย 
  • Interact closely with customers and with the academic community to drive innovation and deliver tailored data science solutions

Collaboration & Communicationย 

  • Build relationships with stakeholders and counterparts to understand business needs and translate them into data science solutions
  • Collaborate closely with engineering, analytics, AI, and product teams to align data science models and insights with broader business goals
  • Communicate findings and model results clearly to non-technical executive audiences, ensuring insights are actionable and understoodย 

Leadership & Influenceย 

  • Establish data science best practices and modeling standards that lift the quality and consistency of analytical work across the teamย 
  • Mentor junior and mid-level data scientists, helping them grow their craft, confidence, and impactย 
  • Bring an AI-forward mindset to your daily work, using tools like Claude, Cursor, and other modern AI assistants to deliver higher-quality work at pace

Whatย You'llย Bringย 

  • 10+ years of data scientist experience with a proven track record of solving complex business problems through data science
  • Bachelor's degree in Statistics, Applied Math, Operations Research, Economics, or a related quantitative field
  • Competency in data querying languages (e.g. SQL) and scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.)
  • Experience with statistical models (e.g., logistic regression, supervised learning approaches) and a solid foundation in machine learning methods
  • Excellent communications skills with non-technical executive audiences, with the ability to translate complex models and findings into clear, actionable insights
  • 1+ year of hands-on experience with AI/ML technologies and modern machine learning frameworks
  • Demonstrated leadership and technical mentoring experience across a team or organization
  • Strong stakeholder communication skills with the ability to translate technical depth across audiences
  • Demonstrable, day-to-day usage and expert knowledge of AI-forward coding tools such as Claude and Cursor
  • Excellent problem-solving skills and the ability to navigate highly ambiguous technical and business challenges with sound judgment
  • Experience with advanced machine learning frameworks and cloud-based data science platforms is a plusย 

Helpful Extras and Unique Skillsย 

  • Experience with handling and modeling data in the healthcare industry is a plusย 
  • AWSย certifications, like Certified Data Engineer - Associate, strongly preferredย ย 

You'llย Do Well Here if You Areย 

  • A doer.ย You see something broken and fix it.ย You'dย rather move on clarity than wait for certainty.ย 
  • A fast learner who knows youย don'tย know everything.ย The AI landscape changes weekly.ย You'reย senior enough to know better and curious enough to keep learning anyway.ย 
  • Direct in a way that makes the work better.ย You give honest feedback.ย You'dย rather haveย theย hard conversation thanย blowย smoke.ย 
  • Obsessed withย craft.ย You know genius is in the details. You shipย exceptional, notย perfect, and youย don'tย put your name onย workย youย wouldn'tย stand behind.ย 
  • Built for ownership.ย You honor commitments, admit mistakes fast, and back your teammates when a decision costs something. No handoffs, no finger-pointing.ย 
  • All in.ย You treat clients' businesses like your own. You take the work seriously without taking yourself seriously.ย 
  • Resourceful when the budget, timeline, or team is tight.ย Constraintsย don'tย slow you down. They sharpen you.ย 
  • Glad to be in the room with people who care as much as you do.ย Our teams average fifteen-plus years of experience. We hire people who push each other to do better work.ย 
    ย 


An offer of employment may be conditional upon successful completion of a background checkย in accordance withย local legislation and ourย candidateย privacy notice. Your current employer will not be contacted without your permission. We are committed to ensuring equal employment opportunities for all job applicants and employees. Employment decisions are based upon job-related reasons regardless of an applicant's race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, marital status, genetic information, protected veteran status, or any other status protected by law.ย