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Data Scientist, AI for Biomedical Imaging

Pay
Multiple pay statements — pay source
Compensation & Benefits: The salary for this position is expected to range between $126,000 and $234,000 USD annually for Senior Expert I, Data Science, and $138,600 and $257,400 USD annually for Senior Expert II, Data Science. The final salary offered is determined based on factors like, but not limited to, relevant skills and experience, and upon joining Novartis will be reviewed periodically. Novartis may change the published salary range based on company and market factors. Your compensation will include a performance-based cash incentive and, depending on the level of the role, eligibility to be considered for annual equity awards.
Salary Range $126,000.00 - $234,000.00 Skills Desired
Read the full posting
Work setting
Not stated
Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting

What you’ll work on

Full posting
  • Lead AI-enabled image analysis strategies with wet-lab scientists

  • Develop, validate and deploy image analysis algorithms for high-content imaging

  • Define benchmarking and evaluation strategies to select image analysis methods

  • Drive adoption of deep learning and vision foundation models for imaging

  • Build scalable, reusable image analysis workflows with data engineering and platform teams

From the employer’s posting
Lead AI-enabled image analysis strategies for complex biological imaging workflows
Develop, validate, and deploy robust image analysis algorithms to characterize cellular, organoid, tissue, and other complex biological phenotypes
define rigorous benchmarking and evaluation strategies to guide method selection
Drive adoption of advanced AI methods for imaging, including deep learning, vision foundation models
Contribute to scalable, reusable image analysis workflows in partnership with other data scientists, data engineering, and platform teams

What you’ll bring

All qualifications

Core experience

  • Demonstrated experience developing and validating image analysis algorithms for biological, biomedical, or pharmaceutical research applications, with practical experience in image segmentation, feature extraction, phenotypic profiling, object classification, or representation learning applied to high-content or high-throughput imaging data.
  • Experience developing or adapting foundation models, self-supervised learning approaches, multimodal AI models, or embedding-based analysis methods (e.g., DINO, CLIP, SAM) for biological imaging data.
  • Practical expertise in designing benchmarking and evaluation strategies to compare image analysis methods and guide rigorous, evidence-based model selection.
  • Familiarity with the drug discovery pipeline, phenotypic screening, translational biology models, or pharmaceutical research processes.
  • Ability to work effectively in Linux-based high-performance computing, cloud, or large-scale data processing environments, with a strong commitment to reproducible research, version control, testing, and data provenance.
  • Familiarity with agentic coding tools and AI-assisted development workflows (e.g., Claude Code, Copilot).
Qualification wording
Demonstrated experience developing and validating image analysis algorithms for biological, biomedical, or pharmaceutical research applications, with practical experience in image segmentation, feature extraction, phenotypic profiling, object classification, or representation learning applied to high-content or high-throughput imaging data.
Experience developing or adapting foundation models, self-supervised learning approaches, multimodal AI models, or embedding-based analysis methods (e.g., DINO, CLIP, SAM) for biological imaging data.
Practical expertise in designing benchmarking and evaluation strategies to compare image analysis methods and guide rigorous, evidence-based model selection.
Familiarity with the drug discovery pipeline, phenotypic screening, translational biology models, or pharmaceutical research processes.
Ability to work effectively in Linux-based high-performance computing, cloud, or large-scale data processing environments, with a strong commitment to reproducible research, version control, testing, and data provenance.
Familiarity with agentic coding tools and AI-assisted development workflows (e.g., Claude Code, Copilot).
Education & alternatives
Essential Requirements: - PhD in computer science, AI, machine learning, biomedical image analysis, computational imaging, data science, or a related quantitative field, with 3+ years of applied experience in AI for bioimaging and computer vision. - Demonstrated experience developing and validating image analysis algorithms for biological, biomedical, or pharmaceutical research applications, with practical experience in image segmentation, feature extraction, phenotypic profiling, object classification, or representation learning applied to high-content or high-throughput imaging data.

Benefits in the posting

Full benefits wording
  • Your compensation will include a performance-based cash incentive and, depending on the level of the role, eligibility to be considered for annual equity awards.
  • US-based eligible employees will receive a comprehensive benefits package that includes health, life and disability benefits, a 401(k) with company contribution and match, and a variety of other benefits. In addition, employees are eligible for a generous time off package including vacation, personal days, holidays and other leaves.
  • EEO Statement:

From the employer’s posting.

Apply at Novartis

Posting record

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Status in our records
Live
First seen by us
Aug 15, 202681 days ago
Recorded sightings
138
Last seen by us
Nov 4, 2026
Employer says posted
Jul 9, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

$118K–$193K is typical

The middle half of what similar US postings state. This one doesn’t list pay.

From 3,721 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 81

Up longer than most. Similar jobs usually come down between day 7 and day 55.

From 10,010 similar postings that came down. Coming down is not always a hire.

Novartis is hiring

46 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Takes jobs down at a usual pace
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • Hugging Face
  • PyTorch
  • scikit-learn
Where the posting names them
- Ability to work effectively in Linux-based high-performance computing, cloud, or large-scale data processing environments, with a strong commitment to reproducible research, version control, testing, and data provenance. - Strong proficiency in Python and the scientific deep learning stack (e.g., PyTorch, Hugging Face, Lightning, MONAI), along with hands-on experience using image analysis tools such as scikit-image, OpenCV, napari, Cellpose, StarDist, InstanSeg, and OME-Zarr. - Self-motivated experienced contributor who thrives in a collaborative, multidisciplinary environment with biologists, imaging scientists, software engineers, and bioinformatics partners, working with appropriate independence and helping shape project direction through both technical expertise and scientific judgment.
Skills Desired Artificial Intelligence (AI), Biostatistics, Change Management, Curious Mindset, Data Governance, Data Literacy, Data Quality, Data Science, Data Visualization, Deep Learning, Graph Algorithms, Learning Agility, Machine Learning (ML), Machine Learning Algorithms, Python (Programming Language), Stakeholder Engagement, Statistical Analysis, Time Series Analysis

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About the role

We file this job under Data Scientist, by the work the posting describes.

Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.

Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.

Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.

US government figures for data scientists

Median yearly pay, May 2025
$120,230
Expected change, 2025 to 2035
34.6% more jobsagainst 3.5% for all jobs

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.

Job description

View original posting ↗

Job Description Summary

The mission of Novartis is to reimagine medicine, and our team advances that mission by applying advanced image analysis, computer vision, and AI methods to early drug discovery. We partner closely with experimental scientists, disease-area teams, data scientists, bioinformatics experts, and platform engineers to extract meaningful biological insight across diverse imaging modalities (high-content screening, custom microscopy platforms) and biological model systems (cellular assays, co-cultures, organoids, tissue models).

To grow this capability, we are seeking a seasoned, innovative, and collaborative data scientist with deep expertise in AI-enabled image analysis to join the Data Science team in Discovery Sciences (DSc) at Novartis Biomedical Research, Cambridge, MA. This role combines hands-on delivery of robust image analysis workflows with advanced AI method development, including biomedical image segmentation, representation learning, foundation models, and scalable deployment. The successful candidate will embed within the research community as the team's scientific lead for imaging-AI, partnering directly with wet-lab scientists to translate complex biological questions into rigorous, reproducible, and impactful analysis strategies.


 

Job Description

Internal Job Title: Senior Expert I/II, Data Science

Position Location: Onsite, Cambridge, MA #LI-Onsite

Role Responsibilities:

  • Lead AI-enabled image analysis strategies for complex biological imaging workflows, acting as the embedded imaging-AI scientific partner working side-by-side with wet-lab scientists to understand emerging assay needs, align approaches with scientific priorities and platform standards, and explain advanced AI concepts in accessible terms.

  • Identify high-impact opportunities where AI can deliver meaningful scientific value and define rigorous benchmarking and evaluation strategies to guide method selection.

  • Develop, validate, and deploy robust image analysis algorithms to characterize cellular, organoid, tissue, and other complex biological phenotypes in high-throughput and high-content imaging data, generating reproducible outputs that support decision-making in drug discovery projects.

  • Drive adoption of advanced AI methods for imaging, including deep learning, vision foundation models, embedding-based phenotyping, segmentation, classification, and multimodal integration, translating state-of-the-art methods into practical, validated workflows that augment expert review and enable scalable interpretation of large, high-dimensional datasets.

  • Contribute to scalable, reusable image analysis workflows in partnership with other data scientists, data engineering, and platform teams, championing best practices across the workflow lifecycle.

Essential Requirements:

  • PhD in computer science, AI, machine learning, biomedical image analysis, computational imaging, data science, or a related quantitative field, with 3+ years of applied experience in AI for bioimaging and computer vision.

  • Demonstrated experience developing and validating image analysis algorithms for biological, biomedical, or pharmaceutical research applications, with practical experience in image segmentation, feature extraction, phenotypic profiling, object classification, or representation learning applied to high-content or high-throughput imaging data.

  • Practical expertise in designing benchmarking and evaluation strategies to compare image analysis methods and guide rigorous, evidence-based model selection.

  • Ability to work effectively in Linux-based high-performance computing, cloud, or large-scale data processing environments, with a strong commitment to reproducible research, version control, testing, and data provenance.

  • Strong proficiency in Python and the scientific deep learning stack (e.g., PyTorch, Hugging Face, Lightning, MONAI), along with hands-on experience using image analysis tools such as scikit-image, OpenCV, napari, Cellpose, StarDist, InstanSeg, and OME-Zarr.

  • Self-motivated experienced contributor who thrives in a collaborative, multidisciplinary environment with biologists, imaging scientists, software engineers, and bioinformatics partners, working with appropriate independence and helping shape project direction through both technical expertise and scientific judgment.

  • Excellent scientific communication and stakeholder engagement skills, including the ability to explain complex AI and image analysis concepts to experimental scientists, project teams, engineers, and non-technical audiences.

Desirable Requirements:

  • Experience developing or adapting foundation models, self-supervised learning approaches, multimodal AI models, or embedding-based analysis methods (e.g., DINO, CLIP, SAM) for biological imaging data.

  • Familiarity with the drug discovery pipeline, phenotypic screening, translational biology models, or pharmaceutical research processes.

  • Demonstrated success in turning project-specific solutions into reusable, scalable workflows or standardized analysis products integrated into enterprise platforms, production pipelines, or user-facing tools.

  • Track record of scientific publication, conference presentations, open-source contributions, or internal technical leadership in AI, computer vision, biomedical image analysis, or related fields.

  • Familiarity with agentic coding tools and AI-assisted development workflows (e.g., Claude Code, Copilot).

Compensation & Benefits:

The salary for this position is expected to range between $126,000 and $234,000 USD annually for Senior Expert I, Data Science, and $138,600 and $257,400 USD annually for Senior Expert II, Data Science. The final salary offered is determined based on factors like, but not limited to, relevant skills and experience, and upon joining Novartis will be reviewed periodically. Novartis may change the published salary range based on company and market factors.


Your compensation will include a performance-based cash incentive and, depending on the level of the role, eligibility to be considered for annual equity awards.


US-based eligible employees will receive a comprehensive benefits package that includes health, life and disability benefits, a 401(k) with company contribution and match, and a variety of other benefits. In addition, employees are eligible for a generous time off package including vacation, personal days, holidays and other leaves.


To learn more about the culture, rewards and benefits we offer our people click here.


 

EEO Statement:

The Novartis Group of Companies are Equal Opportunity Employers. We do not discriminate in recruitment, hiring, training, promotion or other employment practices for reasons of race, color, religion, sex, national origin, age, sexual orientation, gender identity or expression, marital or veteran status, disability, or any other legally protected status. 


 

Accessibility and reasonable accommodations

The Novartis Group of Companies are committed to working with and providing reasonable accommodation to individuals with disabilities. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the application process, or to perform the essential functions of a position, please send an e-mail to us.reasonableaccommodations@novartis.com or call +1(877)395-2339 and let us know the nature of your request and your contact information. Please include the job requisition number in your message.


 

Salary Range

$126,000.00 - $234,000.00


 

Skills Desired

Artificial Intelligence (AI), Biostatistics, Change Management, Curious Mindset, Data Governance, Data Literacy, Data Quality, Data Science, Data Visualization, Deep Learning, Graph Algorithms, Learning Agility, Machine Learning (ML), Machine Learning Algorithms, Python (Programming Language), Stakeholder Engagement, Statistical Analysis, Time Series Analysis
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Pay
Compensation & Benefits: The salary for this position is expected to range between $126,000 and $234,000 USD annually for Senior Expert I, Data Science, and $138,600 and $257,400 USD annually for Senior Expert II, Data Science. The final salary offered is determined based on factors like, but not limited to, relevant skills and experience, and upon joining Novartis will be reviewed periodically. Novartis may change the published salary range based on company and market factors. Your compensation will include a performance-based cash incentive and, depending on the level of the role, eligibility to be considered for annual equity awards.
More source context
Salary Range $126,000.00 - $234,000.00 Skills Desired
Location & working pattern

Cambridge (USA)

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