

Lenmar Consulting Inc
Imaging Data Scientist (Locals Only)
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an Imaging Data Scientist with 4–6 years of experience in computer vision using Python (PyTorch/TensorFlow), focusing on microscopy image processing in a biotech setting. Contract length is unspecified; pay rate is "unknown"; locals only.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
December 17, 2025
🕒 - Duration
Unknown
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🏝️ - Location
Unknown
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Johnston, IA
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🧠 - Skills detailed
#"ETL (Extract #Transform #Load)" #Documentation #AI (Artificial Intelligence) #Strategy #Classification #MLflow #Data Science #Transformers #GitLab #Python #TensorFlow #Image Processing #Code Reviews #PyTorch #Normalization #Batch #GIT #Macros
Role description
Company Description
Pharma
Job 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 end‑to‑end 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
Must Have:
• 4–6 years hands‑on 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, multi‑page TIFFs, z‑stacks, 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.
Nice‑to‑Have
• 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.
Additional Information
All your information will be kept confidential according to EEO guidelines.
Company Description
Pharma
Job 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 end‑to‑end 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
Must Have:
• 4–6 years hands‑on 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, multi‑page TIFFs, z‑stacks, 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.
Nice‑to‑Have
• 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.
Additional Information
All your information will be kept confidential according to EEO guidelines.






