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Internship Data Science R Jobs in Seattle, WA (NOW HIRING)

... for data science interns in the areas of natural language processing, natural language generation, and deep learning. Recognized by Gartner, INC, Harvard Business Review, etc, we are passionate ...

What You'll Bring * 1-3 years of relevant professional work experience in Data Science. * A robust ... A proficiency in at least one programming language (e.g., Java/Python/R). * Experience with tools ...

What You'll Bring * 5 or more years of relevant data science professional work experience; Master ... A proficiency in at least one programming language (e.g., Java/Python/R). * Experience with tools ...

Senior Data Scientist

Seattle, WA · On-site

$120 - $150/hr

... in data science/ML/applied AI/analytics. * Proficient in Python, SQL, R; pandas/NumPy ... scikit‑learn/PyTorch/TensorFlow/statsmodels. * Experience with ML/statistics/NLP/information ...

New

... A senior data science leader who sets and owns the analytics and measurement strategy for SPP ... Advanced, production-grade experience with Python, R, or SQL for analysis, transformation, modeling ...

... A senior data science leader who sets and owns the analytics and measurement strategy for SPP ... Advanced, production-grade experience with Python, R, or SQL for analysis, transformation, modeling ...

Showing results 21-40

Internship Data Science R information

See Seattle, WA salary details

$13

$25

$47

How much do internship data science r jobs pay per hour?

As of Aug 8, 2026, the average hourly pay for internship data science r in Seattle, WA is $25.61, according to ZipRecruiter salary data. Most workers in this role earn between $19.71 and $27.88 per hour, depending on experience, location, and employer.

What types of projects can I expect to work on during an internship data science R?

As a Data Science intern at R, you will typically be involved in projects such as data cleaning, exploratory data analysis, and building predictive models under the guidance of experienced data scientists. You may also contribute to developing data visualizations and presenting insights to stakeholders. Interns often collaborate with cross-functional teams, including software engineers and business analysts, which provides valuable exposure to real-world data challenges and team-based problem solving.

What is the difference between Internship Data Science R vs Data Analyst Intern?

AspectInternship Data Science RData Analyst Intern
Required SkillsProficiency in R, statistical analysis, data visualizationExcel, SQL, basic statistical knowledge
Work EnvironmentData science teams, research projects, analytics departmentsBusiness units, marketing, finance, or operations teams
Industry UsageTech, finance, healthcare, research institutionsRetail, marketing, consulting, finance

Internship Data Science R focuses on applying R programming for statistical analysis and data modeling, often in research or technical environments. Data Analyst Internships emphasize data cleaning, visualization, and reporting using tools like Excel and SQL. Both roles require analytical skills but differ in technical depth and industry focus.

What is an internship data science R?

An Internship Data Science R is a temporary position for students or recent graduates to gain practical experience in data science, with a focus on using the R programming language. Interns typically work under the guidance of experienced data scientists, assisting with data cleaning, analysis, visualization, and possibly building statistical models. This role helps interns develop technical and analytical skills, and provides exposure to real-world data-driven projects, often found in industries like finance, healthcare, or technology.

What are the key skills and qualifications needed to thrive as an internship data science R, and why are they important?

To thrive as an Internship Data Science R, you need a solid grounding in statistics, data analysis, and programming with R, typically supported by coursework or a degree in a quantitative field. Familiarity with R packages (like tidyverse, ggplot2), data visualization tools, and version control systems such as Git is often required. Strong problem-solving skills, attention to detail, and effective communication help interns translate data insights into actionable recommendations. These abilities are crucial for supporting data-driven decision-making and contributing meaningfully to project teams in a professional environment.
What are the most commonly searched types of Data Science R jobs in Seattle, WA? The most popular types of Data Science R jobs in Seattle, WA are:

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted yesterday


Job description

Overview
Fred Hutchinson Cancer Center is an independent, nonprofit organization providing adult cancer treatment and groundbreaking research focused on cancer and infectious diseases. Based in Seattle, Fred Hutch is the only National Cancer Institute-designated cancer center in Washington.
With a track record of global leadership in bone marrow transplantation, HIV/AIDS prevention, immunotherapy and COVID-19 vaccines, Fred Hutch has earned a reputation as one of the world's leading cancer, infectious disease and biomedical research centers. Fred Hutch operates eight clinical care sites that provide medical oncology, infusion, radiation, proton therapy and related services, and network affiliations with hospitals in five states. Together, our fully integrated research and clinical care teams seek to discover new cures to the world's deadliest diseases and make life beyond cancer a reality.
At Fred Hutch we value collaboration, compassion, determination, excellence, innovation, integrity and respect. Our mission is directly tied to the humanity, dignity and inherent value of each employee, patient, community member and supporter. Our commitment to learning across our differences and similarities make us stronger. We seek employees who bring different and innovative ways of seeing the world and solving problems.
The Translational Data Scientist III develops, curates, and analyzes multimodal research datasets that integrate clinical, genomic, and other translational data modalities. This role focuses on building analytically ready datasets and supporting collaborative translational research projects under the guidance of senior scientific and technical leadership.
Working closely with the Translational Data Science Staff Scientist, this position contributes to data harmonization, cohort construction, and cross-domain integration using institutional data platforms and modern data engineering practices. The role emphasizes technical development, structured learning, and applied collaboration with research teams and program level efforts.
This is a hands-on technical role situated at the interface of translational science, data engineering, and research collaboration. This role builds data science solutions, applying LLMs/AI to process, structure, and contextualize health data, and creating data products that are customize to the needs of our translational research programs at Fred Hutch including Clinical trials, Precision Oncology, disease-focused programs, and new data science capabilities both at Fred Hutch and across institutions via the Cancer AI Alliance.
At Fred Hutchinson Cancer Center, all employees are expected to demonstrate a commitment to our values of collaboration, compassion, determination, excellence, innovation, integrity, and respect.
Responsibilities
  • Identify and integrate disparate data sources, both internal and external, including clinical data, genomic data, imaging-derived data, and well-established, publicly available databases.
  • Develop and deploy machine learning algorithms, predictive models, and classification methods to advance cancer research and inform clinical decision making, applying reproducible data processing practices within cloud-based analytic environments.
  • Deliver novel, data-driven insights to improve outcomes in the treatment of cancer, supporting cohort definition, feature engineering, and dataset standardization.
  • Identify areas of growth for the data science initiative and actively engage in enhancing the breadth and reach of data science across the Fred Hutch campus.
  • Collaborate with faculty collaborators, researchers and clinicians to identify high-impact opportunities for data science applications, translating research questions into structured data products and tools
  • Manage data science projects from creation to completion, following established practices for data security, privacy, and compliance.
  • Communicate results to technical and non-technical audiences, contributing to documentation of datasets, assumptions, and transformation logic.

Qualifications
MINIMUM QUALIFICATIONS:
  • Master's or PhD degree in Bioinformatics, Statistics, Biostatistics, Mathematics, Computer Science, Physics, or equivalent required, with a minimum of two years of related experience.
  • Core competency in at least one of the following: genomics, natural language, image processing, medical records or claims.
  • Proficiency in R or Python.
  • Knowledge of statistical analysis, machine learning and predictive modeling.
  • A variety of data formats and markup languages (e.g. XML, JSON, RMarkdown).
  • Unix/Linux and distributed computing.
  • Visualization software: Shiny, Javascript, D3.
  • Code version control (Git, Github) and containers (Docker).
  • Proficiency in at least one common object-oriented programming language (e.g. Java, C++, C#).
  • Experience in application development, visualization, and user design.

PREFERRED QUALIFICATIONS:
  • 3-5 years of related experience.
  • Experience working with clinical, genomic, imaging or other biomedical research data, ideally in Databricks or similar platform.
  • Demonstrated experience using Python, R, or SQL for data analysis and transformation.
  • Familiarity with structured data models and relational data environments.
  • Understanding of reproducible research or analytic workflows.
  • Ability to work collaboratively across scientific and technical teams.
  • Strong organizational and documentation practices.
  • Exposure to clinical data models such as OMOP or similar standardized healthcare data structures.
  • Experience working in a translational research or academic medical environment.
  • Familiarity with cloud-based research computing environments.
  • Experience supporting collaborative research projects or shared data resources.

The annual base salary range for this position is from $126,984 to $200,678, and pay offered will be based on experience and qualifications. This position may be eligibile for relocation assistance.
Although Fred Hutch is not sponsoring most H-1B visas at this time, candidates who already hold an H-1B sponsored by another organization and are currently in the U.S. may be eligible for this position.
Fred Hutchinson Cancer Center offers employees a comprehensive benefits package designed to enhance health, well-being, and financial security. Benefits include medical/vision, dental, flexible spending accounts, life, disability, retirement, family life support, employee assistance program, onsite health clinic, tuition reimbursement, paid vacation (12-22 days per year), paid sick leave (12-25 days per year), paid holidays (13 days per year), and paid parental leave (up to 4 weeks).
Additional Information
We are proud to be an Equal Employment Opportunity (EEO) and Vietnam Era Veterans Readjustment Assistance Act (VEVRAA) Employer. We do not discriminate on the basis of race, color, religion, creed, ancestry, national origin, sex, age, disability (physical or mental), marital or veteran status, genetic information, sexual orientation, gender identity, political ideology, or membership in any other legally protected class. We desire priority referrals of protected veterans. If due to a disability you need assistance/and or a reasonable accommodation during the application or recruiting process, please send a request to Human Resources at hrops@fredhutch.org or by calling 206-667-4700.