Novartis Posted July 9, 2026

Data Scientist, AI for Biomedical Imaging

Cambridge (USA), United States Regular
Data & Digital

Novartis is the source of truth for this posting and owns the application process. We surface normalized context and market comparison you won't find on the original listing.

About this opportunity

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.

Internal Job Title: Senior Expert I/II, Data SciencePosition Location: Onsite, Cambridge, MA #LI-OnsiteRole 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.

Job details

Seniority
Not listed
Function
Data & Digital
Therapeutic area
Not listed
Location
Cambridge (USA), United States
Employment type
Regular

How this role compares

Computed from every other active Data & Digital role in our database, not just this employer's listings.

We currently track 292 comparable Data & Digital roles across 41 biopharma companies.

292Comparable roles tracked
273Currently active
41Companies hiring similar roles
20Countries represented

Salary context

59 of 292 peers report a salary range (USD, annualized)

Peers share this role's job function. This posting doesn't list a seniority level, so peers aren't narrowed by seniority either -- the range below may span more levels than usual.

This roleSubject $126,000/yr – $234,000/yr
Lowest disclosed · Data Engineer, PDS&T CMC · AbbVie $65,500/yr – $125,500/yr
Peer group range $95,500 – $339,950 (median $198,000)

Where these roles are based

Top locations among the 292 comparable roles

India112
United States84
France22
Spain16
United Kingdom8
Canada7

+ 14 more countries

Seniority mix

158 of 292 peers have a known seniority level

Senior57
Manager31
Associate Director20
Director16
Principal16
Associate8
Executive/VP7
Senior Director3

Therapeutic area mix

6 of 292 peers have a known therapeutic area; the rest are genuinely unlabeled, not hidden

Immunology3
Oncology2
Ophthalmology1

Similar opportunities

The closest matches from our peer group, ranked by how similar they are, not how well you'd qualify for them -- treat this as market context, not a guaranteed shortlist; a weak match is labeled as one below.

40%similar
Lilly Indianapolis, Indiana, United States of America
Same function Same country
40%similar
Gilead Sciences, Inc. Foster City, United States Director
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40%similar
Novartis Cambridge (USA), United States
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40%similar
Novartis Cambridge (USA), United States
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40%similar
Novartis Remote Position (USA), United States Director
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40%similar
Regeneron Pharmaceuticals, Inc (USA) Tarrytown, United States Executive/VP
Same function Same country

How we calculate "similar"

No black box, no LLM guesswork: a deterministic score built from four normalized attributes. Here's this role's own peer group at different match levels, so you can see the mechanism, not just the result.

Every comparison starts from the same 100-point budget: 25 for working in the same function, 40 for the same therapeutic area, 20 for the same or adjacent seniority, 15 for the same country. A dimension we can't confirm on both sides contributes nothing, never a guess, never a free pass.

40%
Agentic AI Data Engineer - CMC Data Integration
Lilly · Indianapolis, Indiana, United States of America · Seniority not listed
Function Therapeutic area Seniority Country
40%
AI Scientist – Image Analysis & Digital Pathology
Novartis · Cambridge (USA), United States · Seniority not listed
Function Therapeutic area Seniority Country
40%
Executive Director, Responsible AI & Enterprise Governance
Regeneron Pharmaceuticals, Inc (USA) · Tarrytown, United States · Executive/VP
Function Therapeutic area Seniority Country
40%
Principal Statistical Programmer
Regeneron Pharmaceuticals, Inc (USA) · Warren, United States · Principal
Function Therapeutic area Seniority Country
Unmatched or unknown dimensions score exactly the same: 0 points, never a partial guess. A role we know almost nothing about beyond its function bottoms out at 25%; it never inflates to 100% just because there's little to compare against. Seniority uses a defined ladder (Associate → Manager → Associate Director → Senior → Principal → Director → Senior Director → Executive/VP) so "Director" and "Senior Director" count as adjacent, but "Director" and "Executive/VP" do not.