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Biotech Data Science Jobs (NOW HIRING)

Kellton

Imaging Data Scientist

Johnston, IA

$75/hr

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

Fullpower Technologies

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 ...

Fullpower Technologies, Inc.

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 ...

Harnham

Clinical Data Scientist

San Francisco, CA · Remote

Handle data in a HIPAAaligned manner Key Requirements * 2-5 years in clinical data science, stat programming, or clinical data management * Pharma/Biotech experience * SAS, R, Python, SQL * Realworld ...

BIOMARIN PHARMACEUTICAL

Data Scientist 2

Novato, CA

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 ...

BioMarin Pharmaceutical

Data Scientist 2

Novato, CA · On-site

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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How much do biotech data science jobs pay per year?

As of May 28, 2026, the average yearly pay for 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 is a Biotech Data Science job?

A Biotech Data Science job involves analyzing complex biological and pharmaceutical data to drive research, innovation, and decision-making. Professionals in this field use machine learning, statistical modeling, and bioinformatics tools to extract insights from genomics, clinical trials, and drug discovery datasets. They collaborate with scientists, engineers, and healthcare professionals to improve treatments, develop new therapies, and optimize bioprocesses. Strong programming skills, domain knowledge in biology or biotechnology, and expertise in data analysis are essential for success in this role.

What are the key skills and qualifications needed to thrive in the Biotech Data Science position, and why are they important?

To thrive in Biotech Data Science, you need a solid background in biology or biotechnology, strong statistical and analytical skills, and experience with data analysis languages like Python or R. Familiarity with bioinformatics tools, sequencing platforms, and data visualization software is often expected, with certifications in data science or related fields considered a plus. Excellent problem-solving, communication, and collaboration skills are essential when working across multidisciplinary teams. These competencies enable effective interpretation of complex biological data, driving innovation and insights in the biotech industry.

What are the most common challenges faced by professionals in Biotech Data Science roles?

One of the primary challenges in Biotech Data Science is working with large, complex, and sometimes incomplete biological datasets, which require advanced analytical approaches and careful data curation. Professionals often need to stay current with rapidly evolving technologies and methods, which can be demanding but also rewarding for those who enjoy continuous learning. Collaboration with scientists, engineers, and regulatory teams is common, so adapting communication styles and translating technical findings to diverse audiences is key. Overcoming these challenges leads to meaningful scientific discoveries and significant career growth opportunities.
More about Biotech Data Science jobs
What cities are hiring for Biotech Data Science jobs? Cities with the most 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 Biotech Data Science jobs? States with the most job openings for Biotech Data Science jobs include:
What job categories do people searching Biotech Data Science jobs look for? The top searched job categories for Biotech Data Science jobs are:
Biotech Data Science jobs near you
Infographic showing various Biotech Data Science job openings in the United States as of May 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 83% Physical, and 17% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.

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

Apply