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Volunteer Data Analyst Machine Learning Jobs in Oregon

Natera

Machine Learning Scientist, Multimodal AI

OR · On-site +1

You will build multimodal AI systems that integrate imaging, molecular, and clinical data ... Analyze model outputs to generate reproducible biological and clinical insights * Document ...

Blue River Technology

Machine Learning Engineer, Autonomy

OR · On-site +1

$113K - $202K/yr

Evaluate and improve model performance through rigorous implementation, testing, and analysis of ... Experience in building and deploying full-stack ML pipelines, from data ingestion to model training ...

BetterHelp

Staff Machine Learning Engineer

OR · On-site +1

BetterHelp is looking for a Staff Machine Learning Engineer to join our growing Data team. In this role, you'll help drive a range of impactful, ML-driven initiatives that power our products and ...

Concora Credit Inc.

Data Scientist

Beaverton, OR · On-site

Deep understanding and experience with data analysis, and statistical and machine learning models ... Protect yourself with company-paid Long-Term Disability and voluntary Short-Term Disability Concora ...

Concora Credit Inc.

Data Scientist

Beaverton, OR · On-site

Deep understanding and experience with data analysis, and statistical and machine learning models ... Protect yourself with company-paid Long-Term Disability and voluntary Short-Term Disability Concora ...

Concora Credit Inc.

Data Scientist

Beaverton, OR

Deep understanding and experience with data analysis, and statistical and machine learning models ... Protect yourself with company-paid Long-Term Disability and voluntary Short-Term Disability Concora ...

Instacart

Senior Machine Learning Engineer, Economist

OR · On-site +1

$91K - $116K/yr

... to analyzing the role of prices and product placement in our customers' decision-making. Some of ... Collaborate closely with product managers, data scientists, and other engineers to deeply ...

YipitData (Alternative)

Data Analyst

OR · On-site +1

You have a track record of quickly learning new concepts, particularly complex data methodologies, and building strong mental models of how and why data works * You have tackled complex analytical ...

Concora Credit Inc.

Data Scientist

Beaverton, OR · On-site

Deep understanding and experience with data analysis, and statistical and machine learning models ... Protect yourself with company-paid Long-Term Disability and voluntary Short-Term Disability Concora ...

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All JobsVolunteer Data Analyst Machine Learning JobsVolunteer Data Analyst Machine Learning Jobs in Oregon

Volunteer Data Analyst Machine Learning information

What is the difference between Volunteer Data Analyst Machine Learning vs Volunteer Data Analyst?

AspectVolunteer Data Analyst Machine LearningVolunteer Data Analyst
Required skillsData analysis, machine learning, programming (Python/R), statistical knowledgeData analysis, Excel, basic statistics, data visualization
Work environmentTech-focused, project-based, collaborative teamsNon-profit, research, community projects
Common employersTech companies, research institutions, startupsNon-profits, NGOs, community organizations

Volunteer Data Analyst Machine Learning roles typically require programming and machine learning expertise, working on advanced data projects. Volunteer Data Analysts focus on data cleaning, visualization, and basic analysis. Both roles support organizations but differ in technical complexity and scope.

Volunteer Data Analyst Machine Learning jobs near you

Machine Learning Scientist, Multimodal AI

OR • On-site, Remote

Natera
Biotechnology Research and Development • 1 - 5K employees
Learn more about Nateraexternal

Full-time

Re-posted 12 days ago

Natera rating

7.8

Company rating: 7.8 out of 10

Based on 39 frontline employees who took The Breakroom Quiz

56th of 121 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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