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Weekend Biotech Data Science Jobs (NOW HIRING)

Partner with DH stakeholders (biotech & breeding, Genome Technology Discovery, Data Science) to align deliverables with deployment milestones. * Maintain IP & data stewardship practices consistent ...

Data Scientist

Santa Cruz, CA · On-site

$130K - $170K/yr

... and biotechnology. Fullpower's platform is vetted and deployed as a PaaS, backed by a patent ... The ideal candidate will have a strong background in machine learning and data science and a proven ...

Since 1980, we've helped pioneer the world of biotech in our fight against the world's toughest ... Our award-winning culture is collaborative, innovative, and science based. If you have a passion ...

Data Scientist

Santa Cruz, CA · Remote

$130K - $170K/yr

... and biotechnology. Fullpower's platform is vetted and deployed as a PaaS, backed by a patent ... The ideal candidate will have a strong background in machine learning and data science and a proven ...

Responsibilities Data Scientists at Mayo Clinic perform detailed analysis of large bodies of ... PM) Weekend Schedule No Weekends International Assignment No Site Description Just as our ...

Leading, using and developing data science, machine learning, and artificial intelligence ... Biotech / Pharma experience WORK METHODOLOGY: * Full on site job in Juncos, PR * Full time job

MSAT Data Science Engineer

Newark, CA · On-site

$120K - $140K/yr

Allogene Therapeutics, with headquarters in South San Francisco, is a clinical-stage biotechnology ... We are seeking a highly motivated individual to join us as a Data Science Engineer, Manufacturing ...

MSAT Data Science Engineer

Newark, CA · On-site

$120K - $140K/yr

Allogene Therapeutics, with headquarters in South San Francisco, is a clinical-stage biotechnology ... We are seeking a highly motivated individual to join us as a Data Science Engineer, Manufacturing ...

This role blends advanced technical skills in Data Science-covering statistics, Modelling, AI/ML-with deep domain expertise in highly regulated Biotech industry. These should be complemented by soft ...

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Weekend Biotech Data Science information

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$37.5K

$122.7K

$196.5K

How much do weekend biotech data science jobs pay per year?

As of Jun 25, 2026, the average yearly pay for weekend biotech data science 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 cities are hiring for Weekend Biotech Data Science jobs? Cities with the most Weekend Biotech Data Science job openings:
What are the most commonly searched types of Biotech Data Science jobs? The most popular types of Biotech Data Science jobs are:
What states have the most Weekend Biotech Data Science jobs? States with the most job openings for Weekend Biotech Data Science jobs include:

Imaging Data Scientist

Kellton

Johnston, IA • On-site

$75/hr

Other

Posted 27 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