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Intern Data Scientist Machine Learning Jobs in Oregon

Natera

Machine Learning Scientist, Multimodal AI

OR · On-site +1

Natera is hiring a Machine Learning Scientist to join our AI and computational biology team. This ... You will build multimodal AI systems that integrate imaging, molecular, and clinical data ...

phData

Machine Learning Principal Solutions Architect

OR · On-site +1

We are looking for a Principal Solutions Architect to join our Machine Learning team. In this role ... Translate business and data science requirements into scalable, secure, and resilient architectures ...

Varsity Tutors

Machine Learning Tutor

Portland, OR · Remote

$18 - $40/hr

... preparing students for data science roles and advanced AI coursework. * Conceptual Teaching ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Eugene, OR · Remote

$18 - $40/hr

... preparing students for data science roles and advanced AI coursework. * Conceptual Teaching ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

OR · Remote

$18 - $40/hr

... preparing students for data science roles and advanced AI coursework. * Conceptual Teaching ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

BetterHelp

Machine Learning Engineer

OR · On-site +1

As a Machine Learning at BetterHelp, you'll join a diverse team of licensed clinicians, engineers ... Partner closely with Product, Engineering, and Data Science teams to identify opportunities where ...

Netflix

Machine Learning Scientist (L6) - Live Ads

OR · On-site +1

Our Team The Ad Supply & Decisioning team within the Ads Data Science and Engineering (DSE ... We are looking for a Machine Learning Scientist 6 to serve as a vertical technical lead across our ...

Upstart

Staff/Principal Machine Learning Engineer

OR · On-site +1

As a Principal Machine Learning Engineer, you will work at the intersection of applied ML and platform engineering-collaborating closely with Research Scientists, Data Scientists, and ML Platform ...

Anno.ai

Senior Machine Learning Engineer

OR · On-site +1

$104K - $143K/yr

Bachelor's degree in Computer Science, Electrical Engineering, Data Science, or a related technical ... software engineering, machine learning engineering, MLOps, or related roles * Experience ...

Upstart

Staff Machine Learning Model Risk Specialist

OR · On-site +1

$98K/yr

Internship or project experience related to model risk management, model validation, machine learning, or data science. * Basic understanding of AI/ML methodologies such as tree-based models and ...

New

Intel

Senior AI / Data Science Engineer

Hillsboro, OR

$115K - $156K/yr

Lead development of advanced AI, Machine Learning, and Generative AI solutions that address ... Data Science, Machine Learning, Artificial Intelligence, Advanced Analytics. Performing yield ...

Waymark

Data/AI Scientist II

OR · On-site +1

$95K - $127K/yr

Solid foundations in statistical and machine learning methods, including classical ML and an ... of industry data science experience * Exposure to healthcare data (claims or EHR) through ...

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All JobsIntern Data Scientist Machine Learning JobsIntern Data Scientist Machine Learning Jobs in Oregon

Intern Data Scientist Machine Learning information

What does an intern data scientist machine learning do?

An Intern Data Scientist in Machine Learning assists in analyzing large datasets, building predictive models, and extracting insights to support business decisions. They often work under the guidance of experienced data scientists to clean data, implement machine learning algorithms, and evaluate model performance. Their responsibilities may also include data visualization and reporting findings to team members. This role provides hands-on experience with real-world data science problems and tools, helping interns develop essential technical and analytical skills.

What types of projects and responsibilities can an intern data scientist machine learning expect to work on?

As an Intern Data Scientist focused on Machine Learning, you will often assist in tasks such as data cleaning, feature engineering, and developing or testing machine learning models under the supervision of senior team members. You may also be involved in exploratory data analysis and help interpret model results to provide actionable insights. Interns typically collaborate closely with data engineers, analysts, and software developers, gaining exposure to end-to-end machine learning pipelines. This hands-on experience provides valuable learning opportunities and helps build the foundational skills needed for future roles in data science.

What are the key skills and qualifications needed to thrive as an intern data scientist machine learning, and why are they important?

To thrive as an Intern Data Scientist (Machine Learning), you need a solid understanding of statistics, programming skills (typically in Python or R), and foundational knowledge of machine learning algorithms, often supported by coursework or relevant projects. Familiarity with tools like scikit-learn, TensorFlow, Jupyter notebooks, and version control systems (e.g., Git) is commonly expected. Strong analytical thinking, curiosity, and effective communication skills help you interpret data insights and work collaboratively within a team. These abilities are crucial for translating data into actionable solutions and contributing to impactful machine learning projects.

What is the difference between Intern Data Scientist Machine Learning vs Intern Data Analyst?

AspectIntern Data Scientist Machine LearningIntern Data Analyst
Required SkillsBasic programming, statistics, machine learning conceptsData analysis, Excel, SQL, visualization tools
Work EnvironmentResearch-focused, model development, algorithm testingData cleaning, reporting, dashboard creation
Common Industry UsageTech, finance, healthcareRetail, marketing, finance

Intern Data Scientist Machine Learning roles focus on developing and testing machine learning models, requiring knowledge of algorithms and programming. Intern Data Analyst positions emphasize data cleaning, analysis, and visualization. Both roles are entry-level but differ in technical depth and project focus, catering to different career paths within data-driven industries.

What are the most commonly searched types of Data Scientist Machine Learning jobs in Oregon?

The most popular types of Data Scientist Machine Learning jobs in Oregon are:

What are popular job titles related to Intern Data Scientist Machine Learning jobs in Oregon?

For Intern Data Scientist Machine Learning jobs in Oregon, the most frequently searched job titles are:

What job categories do people searching Intern Data Scientist Machine Learning jobs in Oregon look for?

The top searched job categories for Intern Data Scientist Machine Learning jobs in Oregon are:

What cities in Oregon are hiring for Intern Data Scientist Machine Learning jobs?

Cities in Oregon with the most Intern Data Scientist Machine Learning job openings:

Intern Data Scientist Machine Learning jobs near you
Infographic showing various Intern Data Scientist Machine Learning job openings in Oregon as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, 2% Contract, and 1% Nights. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Machine Learning Scientist, Multimodal AI

Natera

OR • On-site, Remote

Full-time

Re-posted 24 days ago

Natera rating

7.7

Company rating: 7.7 out of 10

Based on 38 frontline employees who took The Breakroom Quiz

57th of 120 rated laboratories

Job description

POSITION SUMMARY:

Natera is hiring a Machine Learning Scientist to join our AI and computational biology team. This role develops and deploys deep learning models across digital pathology, genomics, transcriptomics, and cell-free DNA (cfDNA) modalities. You will build multimodal AI systems that integrate imaging, molecular, and clinical data, leveraging proprietary genomic and clinical datasets. You will collaborate with scientists, pathologists, bioinformaticians, and software engineers to scale machine learning approaches that advance personalized oncology diagnostics and tumor-informed minimal residual disease (MRD) testing.

PRIMARY RESPONSIBILITIES:

  • Design, implement, and evaluate deep learning models across biomedical data modalities, including histopathology imaging, genomic sequencing, transcriptomics, and cfDNA features
  • Develop multimodal AI architectures that integrate H&E whole-slide imaging data with molecular and clinical data sources
  • Build scalable, production-quality machine learning workflows and pipelines using cloud infrastructure (AWS)
  • Apply modern machine learning techniques including convolutional neural networks (CNNs), vision transformers (ViTs), sequence transformers, representation learning, and foundation model fine-tuning
  • Collaborate across technical and clinical teams to translate machine learning prototypes into validated tools
  • Analyze model outputs to generate reproducible biological and clinical insights
  • Document pipelines thoroughly and communicate data-driven findings clearly to cross-functional stakeholders

QUALIFICATIONS:

  • PhD in Computer Science, Computational Biology, Biomedical Engineering, Bioinformatics, Statistics, or a related quantitative discipline with a focus on machine learning or AI
  • Core experience developing machine learning models for biomedical applications, specifically in medical imaging, computational pathology, genomics, transcriptomics, multi-omics, or molecular diagnostics
  • Hands-on expertise with PyTorch and strong production-level programming skills in Python
  • Practical application of deep learning architectures such as CNNs, transformers, attention mechanisms, and representation learning
  • Experience managing datasets and training workflows within distributed or cloud computing environments (AWS)
  • Proven ability to take ownership of research projects and translate prototypes into robust, deployment-ready workflows
  • Experience adapting pre-trained foundation models for downstream biomedical applications

PREFERRED QUALIFICATIONS:

  • Experience integrating imaging, molecular, and clinical data within unified multimodal machine learning frameworks
  • Technical familiarity with DNA sequencing, RNA sequencing, methylation, and ctDNA assays
  • Hands-on experience with digital pathology software and whole-slide imaging analysis
  • Exposure to survival modeling, longitudinal prediction, or time-to-event modeling
  • Experience applying self-supervised learning, weakly supervised learning, or multiple instance learning (MIL) to clinical data
  • Domain knowledge in oncology, biomarker discovery, or clinical precision medicine
  • Track record of peer-reviewed publications in machine learning or computational biology conferences and journals (e.g., NeurIPS, ICML, CVPR, MICCAI, Nature Biomedical Engineering)

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