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Imaging Data Scientist Jobs (NOW HIRING)

Kellton

Imaging Data Scientist

Johnston, IA

$75/hr

Imaging Data Scientist Location: Johnston, IA 50131 Locals only within 50-mile required onsite T/W/TH each week Duration: 12 months + extensions Max Pay Rate: $75/hr W2 (No Benefits) - DOE No C2C at ...

University of Florida

Data Scientist III

Gainesville, FL · On-site

$82K - $85K/yr

They will ensure data and model quality, integrity, and robustness, and will contribute to scientific publications related to healthcare/ imaging AI research. Essential Functions; • Maintaining a ...

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How much do imaging data scientist jobs pay per year?

As of May 28, 2026, the average yearly pay for imaging data scientist in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

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

To thrive as an Imaging Data Scientist, you need a strong background in computer science, mathematics, and image analysis, often supported by an advanced degree in a related field. Familiarity with programming languages like Python or MATLAB, machine learning frameworks, and image processing tools such as OpenCV or ITK is typically required. Strong analytical thinking, attention to detail, and effective communication skills help distinguish top performers in this role. These skills and qualities are crucial for developing accurate image-based models, collaborating with interdisciplinary teams, and translating complex data into actionable insights.

How does an Imaging Data Scientist typically collaborate with other teams in a research or clinical setting?

Imaging Data Scientists frequently work alongside radiologists, clinicians, and software engineers to develop and refine algorithms for analyzing medical images. Collaboration often involves regular meetings to interpret imaging data needs, share findings, and troubleshoot issues related to data quality or algorithm performance. They may also work closely with data engineers to ensure efficient data storage and retrieval, and with project managers to align on timelines and deliverables. This cross-disciplinary teamwork ensures that imaging solutions are both scientifically robust and practically applicable in clinical workflows.

What is an Imaging Data Scientist?

An Imaging Data Scientist is a professional who specializes in analyzing and interpreting data from various imaging sources, such as medical scans, satellite images, or industrial photographs. They use advanced data analysis, machine learning, and image processing techniques to extract meaningful insights from complex image data. These scientists often collaborate with experts in fields like healthcare, remote sensing, or manufacturing to support decision-making and innovation. Their work can involve tasks such as developing algorithms for image classification, segmentation, or enhancement. The role requires strong skills in programming, statistics, and domain-specific knowledge.

What is the difference between Imaging Data Scientist vs Medical Data Scientist?

AspectImaging Data ScientistMedical Data Scientist
CredentialsTypically requires a degree in data science, computer science, or related fields; familiarity with imaging softwareRequires a degree in data science, biostatistics, or healthcare-related fields; often with knowledge of medical terminologies
Work EnvironmentWorks in healthcare, research institutions, or tech companies focusing on imaging dataWorks in hospitals, healthcare organizations, or biotech firms analyzing medical data
Industry UsageUsed in medical imaging analysis, radiology, and diagnostic researchApplied in clinical research, patient data analysis, and healthcare decision support

Imaging Data Scientists focus on analyzing medical images like MRI, CT scans, and X-rays, utilizing machine learning and image processing techniques. Medical Data Scientists work with broader healthcare data, including electronic health records and clinical data. While both roles require data science skills, Imaging Data Scientists specialize in imaging modalities, making their roles distinct yet overlapping in healthcare analytics.

More about Imaging Data Scientist jobs
What cities are hiring for Imaging Data Scientist jobs? Cities with the most Imaging Data Scientist job openings:
What states have the most Imaging Data Scientist jobs? States with the most job openings for Imaging Data Scientist jobs include:
What job categories do people searching Imaging Data Scientist jobs look for? The top searched job categories for Imaging Data Scientist jobs are:
Imaging Data Scientist jobs near you

Imaging Data Scientist

Kellton

Johnston, IA

$75/hr

Other

Posted 28 days ago

Job description

Imaging Data Scientist
Location: Johnston, IA 50131 Locals only within 50-mile required onsite T/W/TH each week
Duration: 12 months + extensions
Max Pay Rate: $75/hr W2 (No Benefits) - DOE

No C2C at this time

Project Scope and Brief Description

Work at the intersection of plant cell biology and applied AI to build, productionize, and maintain computer vision pipelines that accelerate Doubled Haploid (DH) breeding in Biotechnology. The contractor will contribute to endtoend imaging and analytics from microscopy microspore detection to macroscopic structure assessment and plantlet characterization supporting decisions that reduce cycle time and cost in DH programs. Solutions will be developed primarily in Python, integrated with our repositories and workflow tooling, and aligned with Biotech strategy initiatives

Responsibilities:

  • Design & deliver deep learning-based CV models for microscopy and macroscopic assays (detection, segmentation, classification) with measurable accuracy, robustness, and throughput.
  • Build productionready pipelines in Python (data ingest, preprocessing, augmentation, inference, batch processing), integrated with GitLab repos and experiment tracking; ensure reproducibility and documentation.
  • Implement hyperspectral analysis workflows (band selection, normalization, feature extraction, model training).
  • Harmonize imaging acquisition with analysis by collaborating with biology teams to standardize microscopy/RGB/hyperspectral capture and file formats (e.g., FIJI/ImageJ for zstacks; autoscale practices).
  • Quantify model performance (precision/recall, F1, ROC/AUC, calibration) and write clear reports/posters for DH sessions; support factchecking in presentations.
  • Operationalize at scale: batch processing of tens of thousands of structures/images; optimize inference (e.g., torch.compile, mixed precision) and monitor resource usage.
  • Partner with DH stakeholders (biotech & breeding, Genome Technology Discovery, Data Science) to align deliverables with deployment milestones.
  • Maintain IP & data stewardship practices consistent with internal strategy; avoid disclosure of confidential protocols while enabling model reuse

Must Have:

  • 4 6 years handson in computer vision with Python (PyTorch/TensorFlow), including detection/segmentation/classification for scientific or industrial imaging.
  • Proven ability to productionize models: Git/GitLab, code reviews, CICD basics, experiment tracking (MLFlow or equivalent), reproducible data/experiments, and clear documentation.
  • Experience with microscopy image processing, multipage TIFFs, zstacks, autoscale/normalization, and image quality challenges.
  • Familiarity with hyperspectral or multispectral imaging pipelines (preprocessing, dimensionality reduction, modeling) applied to plant or biological materials.
  • Track record of measurable model performance reporting and communicating results via posters/presentations for technical audiences.

NicetoHave

  • Vision Transformers (ViT) and modern YOLO workflows for microscopy/macroscopic tasks; comfort with infer tooling.
  • Experience optimizing inference (e.g., torch.compile, mixed precision) and scaling batch workflows.
  • Domain familiarity with Biotech breeding workflows.
  • Collaboration with discovery and strategy teams; ability to work across biology, engineering, and data science groups.

Soft Skills

  • Strong stakeholder communication and the ability to translate biology & process constraints into CV requirements; comfortable triaging and prioritizing rapidly in active programs.
  • Ownership mindset around documentation, reproducibility, and IPaware sharing.
  • Curious and learning mindset
  • Technical leadership experience

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