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# Image Data Scientist

- **Company:** Pride Global
- **Location:** South San Francisco, CA, United States
- **Experience:** Expert
- **Salary:** $104,000.0 - $132,746.0
- **Contract:** Temporary contract
- **Skills:** Artificial Intelligence, Airflow, Amazon Elastic Compute Cloud, Computer Vision, Cloud Computing, Image Analysis, Data Visualization, Java GUIs, Python (Programming Language), Machine Learning, NumPy, Object Detection, OpenCV, Tensorflow, Standard Widget Toolkits, Workflow Management Systems, High Performance Computing, Pytorch, Deep Learning, Keras, Git, Pandas, Scikit Learn, Statistics Packages, Slurm, Feature Extraction
- **Published:** May 29, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=b21611942823dfd9

## About the Role

Do you have experience in Statistical analysis tools?, Do you have a Master's degree?, * Strong programming in Python (NumPy, Pandas, Scikit-learn, OpenCV)

 * Solid foundation in computer vision and image analysis
 * Hands-on experience with whole-slide image (WSI) processing (e.g., OpenSlide)
 * Experience with machine learning for image classification and segmentation
 * Proficiency with Git and collaborative development workflows
 * Strong communication and ability to work in cross-disciplinary teams
 * Master's or PhD in a relevant field OR minimum 5+ years of relevant experience

Preferred Skills

 * Deep learning expertise using PyTorch / TensorFlow / Keras
 * Experience with instance segmentation and object detection frameworks (e.g., Detectron2)
 * Familiarity with HPC environments and SLURM
 * Experience with digital pathology tools (e.g., HALO, Visiopharm, QuPath)
 * Workflow orchestration tools (e.g., Airflow, Dagster)
 * Cloud computing experience (especially AWS EC2)
 * Ability to build simple GUIs (Tkinter / PyQt)

## Description

* Develop and implement image processing pipelines for histopathology and whole-slide images (WSI)
 * Apply classical computer vision and machine learning techniques for image classification, segmentation, and feature extraction
 * Design and deploy deep learning models for digital pathology tasks (e.g., instance/semantic segmentation)
 * Process and analyze gigapixel whole-slide images using tools such as OpenSlide
 * Collaborate with pathologists to translate biological questions into computational workflows
 * Perform statistical analysis and data visualization to support research findings
 * Contribute to AI-driven tool development for pathology interpretation and risk assessment


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