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R Data Scientist Assistant Jobs in Oregon (NOW HIRING)

Experience with Python, R, SQL, and data science libraries (e.g., Pandas, NumPy, SciPy) is required. * Personnel must have experience in cloud-based AI/ML tools, such as AWS SageMaker or Azure ...

Experience with Python, R, SQL, and data science libraries (e.g., Pandas, NumPy, SciPy) is required. * Personnel must have experience in cloud-based AI/ML tools, such as AWS SageMaker or Azure ...

Data Scientist

OR · On-site +1

Experience with Python, R, SQL, and data science libraries (e.g., Pandas, NumPy, SciPy) is required. * Personnel must have experience in cloud-based AI/ML tools, such as AWS SageMaker or Azure ...

OR · On-site

... * Assist on research development projects and data science project plans for clients and internal ... A strong understanding of a statistical programming language such as R or Python * Expertise ...

Advanced knowledge of Python or R and experience with common data science libraries such as lightgbm, scikit-learn, pandas, etc.. * Deep understanding of model deployment requirements for scalable ...

OR · On-site

The Sr. Data Scientist wilil play an important role in this strategic initiative. This person will ... Advanced experience with Python, R, SQL, and any other related programs for executing the above ...

Advanced knowledge of Python or R and experience with common data science libraries such as lightgbm, scikit-learn, pandas, etc.. * Deep understanding of model deployment requirements for scalable ...

OR · On-site

Our Data Scientists not only code up solutions to real-world problems but also participate in ... e.g., R, Pyspark, JavaScript, etc.). An ideal candidate is excited to learn complex new ...

OR · On-site

Proficient in Python/R and SQL for data analysis, predictive modeling, and optimization workflows ... Bachelor's degree in Data Science, Mathematics, Statistics, Computer Science, or related field.

OR · On-site

Roles are open at both the L5 (Senior Data Scientist I) and L6 (Senior Data Scientist II) levels ... Ability to write efficient and eloquent code in Python or R. * A desire to build and improve ...

... problems. * Assist in exploring new data sources, research, and models under the direction of ... science tools (R, SQL, TensorFlow,PyTorch). * Experience with prompt engineering for LLMs * You ...

OR · On-site

$113K - $188K/yr

Data Science Consulting Travel Required: None Clearance Required: Active Public Trust What You Will ... R * Experience integrating AI/ML solutions (e.g., LLMs, predictive models) into production ...

OR

$372K - $600K/yr

Our Commerce Data Science team works with a broad range of collaborators and stakeholders ... Strong data manipulation and quantitative programming skills in SQL and Python or R * Experience ...

OR · On-site

Working knowledge of Python or R and experience with data science libraries such as lightgbm, scikit-learn, pandas, numpy etc. * Strong communication and presentation skills with an ability to relate ...

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R Data Scientist Assistant information

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

To thrive as an R Data Scientist Assistant, you need a solid understanding of statistics, data analysis, and proficiency in the R programming language, often supported by coursework in data science or a related field. Familiarity with tools such as RStudio, data visualization packages like ggplot2, and version control systems like Git is typically expected. Strong attention to detail, critical thinking, and effective communication skills help you interpret data and work collaboratively with teams. These skills are crucial for ensuring accurate data analysis, efficient workflow, and actionable insights for business or research objectives.

What are the typical collaboration dynamics between an R Data Scientist Assistant and senior data scientists or analysts?

As an R Data Scientist Assistant, you will often work closely with senior data scientists and analysts, supporting them by preparing datasets, performing initial data cleaning, and conducting exploratory analyses using R. You may be responsible for creating reproducible scripts, visualizing results, and documenting your workflow. Regular meetings and code reviews are common, providing opportunities to learn best practices and receive feedback. This collaborative environment helps you build technical skills and understand how your contributions fit into larger data-driven projects.

What are R Data Scientist Assistants?

R Data Scientist Assistants are professionals who support data scientists by performing data cleaning, analysis, and visualization tasks using the R programming language. They help prepare datasets, create scripts, generate reports, and may assist in implementing machine learning models. Their role is crucial in ensuring data quality and streamlining the workflow, allowing data scientists to focus on more complex analyses. This position typically requires a strong foundation in statistics, programming in R, and good communication skills.

What is the difference between R Data Scientist Assistant vs Data Analyst?

AspectR Data Scientist AssistantData Analyst
Required CredentialsBachelor's in Data Science, Statistics, or related field; familiarity with RBachelor's in Data, Statistics, Business, or related field; proficiency in data tools
Work EnvironmentResearch labs, tech companies, analytics teamsBusiness settings, marketing, finance, healthcare
Employer & Industry UsageTech firms, research institutions, analytics departmentsCorporations, consulting firms, government agencies
Common Search & ComparisonOften compared for entry-level data roles involving RCompared for data interpretation and reporting tasks

The R Data Scientist Assistant typically focuses on supporting data science projects using R, requiring programming skills and statistical knowledge. Data Analysts often handle data interpretation, reporting, and visualization across various industries. While both roles require analytical skills, the assistant role emphasizes programming and statistical modeling, whereas the analyst role centers on data reporting and business insights.

What are the most commonly searched types of R Data Scientist jobs in Oregon? The most popular types of R Data Scientist jobs in Oregon are:
Infographic showing various R Data Scientist Assistant job openings in Oregon as of May 2026, with employment types broken down into 94% Full Time, and 6% Part Time. Highlights an 87% In-person, and 13% Remote job distribution.

Full-time

Posted 13 days ago


Job description

We are looking for a Data Scientist to analyze large amounts of raw information to find patterns that will help improve our company. We will rely on you to build data products to extract valuable business insights.
In this role, you should be highly analytical with a knack for analysis, math, and statistics. Critical thinking and problem-solving skills are essential for interpreting data. We also want to see a passion for machine learning and research.
Your goal will be to help our company analyze trends to make better decisions.
Responsibilities
Identify valuable data sources and automate collection processes
Undertake to preprocess of structured and unstructured data
Analyze large amounts of information to discover trends and patterns
Build predictive models and machine-learning algorithms
Combine models through ensemble modeling
Present information using data visualization techniques
Propose solutions and strategies to business challenges
Collaborate with engineering and product development teams
Requirements and skills
Proven experience as a Data Scientist or Data Analyst
Experience in data mining
Understanding of machine learning and operations research
Knowledge of R, SQL, and Python; familiarity with Scala, Java, or C++ is an asset
Experience using business intelligence tools (e.g. Tableau) and data frameworks (e.g. Hadoop)
Analytical mind and business acumen
Strong math skills (e.g. statistics, algebra)
Problem-solving aptitude
Excellent communication and presentation skills
BSc/BA in Computer Science, Engineering, or relevant field; a graduate degree in Data Science or other quantitative field is preferred