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Job Description
Expert II / Senior Expert I, Data Science, New Targets Novartis - 4.1 Cambridge, MA Job Details Full-time $114,100 - $234,000 a year 1 day ago Benefits Health insurance 401(k) matching Qualifications AI models Statistics Computational research Data Integration (Data management) Statistics Tooling Workflow management (operations management method) High-performance computing clusters AI tools proficiency Machine intelligence Machine learning (ML) fundamentals Cross-functional collaboration Bioinformatics data analysis Cross-functional communication Statistical analysis tools Biostatistical modeling Full Job Description Summary #
LI-Hybrid Location:
Cambridge, Massachusetts, United States This role is based in Cambridge, MA. Novartis is unable to offer relocation support for this role. Please only apply if this location is accessible for you. The Oncology Data Science team in Biomedical Research works at the intersection of oncology drug discovery, computational biology, AI/ML, and data engineering to advance innovative therapeutics across drug modalities. We are seeking a highly motivated Senior Expert I / Expert II, Data Science to join the New Targets team as an experienced individual contributor. This role will apply advanced statistical, machine learning, and computational approaches to generate biological insight from complex multi-modal datasets and support target discovery and prioritization. The successful candidate will bring expertise across multiple omics modalities and data types, including spatial transcriptomics, proteomics, digital pathology, mIF or similar high-plex tissue imaging modalities as well as other high-dimensional molecular data such as bulk and single-cell RNA-seq, WES, WGS, etc. The role requires both scientific depth and technical fluency, including modern AI-enabled workflows that improve productivity, reproducibility, and scale. About the Role Key Responsibilities Lead the analysis and integration of multi-modal omics datasets, including spatial transcriptomics, proteomics, high-plex imaging, and sequencing-based platforms (e.g., RNA-seq, scRNA-seq, WES, WGS) Develop and apply advanced statistical, machine learning, and AI-driven methods to extract actionable biological insights from complex datasets Partner with cross-functional teams to design and execute studies supporting target identification, validation, and translational research Build and contribute to scalable, reproducible data science workflows and computational pipelines Ensure high standards of data quality, reproducibility, and scientific rigor in all analyses Evaluate and implement emerging technologies, including AI-assisted coding platforms and agentic tools, to enhance team effectiveness and innovation Communicate scientific findings clearly to both technical and non-technical stakeholders Contribute to knowledge sharing, best practices, and continuous improvement within the computational biology and data science community Essential Requirements PhD (or equivalent experience) in Computational Biology, Bioinformatics, Statistics, Computer Science, or a related quantitative discipline Demonstrated expertise in the analysis of complex omics datasets and at least one of the following: spatial transcriptomics, proteomics, or digital pathology Strong programming skills in R and/or Python Experience working with high-performance computing (HPC) environments and workflow management systems Deep understanding of statistical modeling, machine learning, and data integration methodologies Familiarity with AI-assisted coding tools and modern data science productivity platforms Strong collaboration and communication skills, with the ability to work effectively in multidisciplinary teams The salary for this position is expected to range between:
Expert II:
[$114,100 - $211,900/year]
Senior Expert I:
[$126,000 - $234,000/year] The final salary and level 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.
Why Novartis:
Helping people with disease and their families takes more than innovative science. It takes a community of smart, passionate people like you. Collaborating, supporting and inspiring each other. Combining to achieve breakthroughs that change patients' lives. Ready to create a brighter future together?
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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 & 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 [email protected] 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. Division Biomedical Research Business Unit Research Location USA State Massachusetts Site Cambridge (USA) Company / Legal Entity U175 (FCRS = US175) Novartis Institutes for BioMedical Research, Inc. Functional Area Data and Digital Job Type Full time Employment Type Regular Shift Work No
