Senior Expert I, Data Science

Major accountabilities:

• Collaborate closely with interdisciplinary wet-lab and computational scientists to design, analyze, and interpret high-dimensional biological data (e.g., bulk RNA-seq, DNA-seq, CRISPR, drug screening) to inform critical project decision.
• Lead profiling strategies and analysis of high-throughput genomic and phenotypic screening data to inform patient stratification and mechanism of resistance, in support of drug discovery and development.
• Integrate multi-modal internal and external preclinical datasets (e.g., genomics, transcriptomics, pharmacology, and functional screens) to produce translationally relevant insights.
  Apply advanced bioinformatics and machine learning approaches across multi-modal datasets to uncover novel, actionable biological insights and therapeutic hypotheses.
• Develop and implement innovative analytical methods to support emerging technologies and to effectively integrate, interrogate, and visualize multi-dimensional datasets.
• Drive oncology research by leveraging data mining and genomic profiling to identify novel targets for induced proximity modality, elucidate mechanism of action and support patient stratification strategies.
• Communicate integrative analyses and key findings clearly and effectively to diverse audiences, including cross-functional scientific teams and stakeholders.

Qualifications:

• PhD in Computational Biology, System Biology, Bioinformatics, Data/Computer Science, or related field with relevant industry experience.
• Strong knowledge of cancer biology and multi-modal data types such as genomics, transcriptomics, proteomics and phenotypic screening data.
  Proficiency in one or more programming languages for bioinformatics applications (e.g., Python, R) with experience in UNIX/Linux environment, version control, and reproducible workflows.
  Demonstrated statistical rigor and analytic depth in the analysis of high-dimensional omics datasets (e.g., bulk and single-cell transcriptomics, genomics).
• Demonstrated experience leveraging AI‑assisted coding tools (e.g., copilots, code generators, and LLM-based workflows) to accelerate data analysis, model development, and reproducible scientific pipelines.
• Familiarity with data workflows, including preclinical biomarker discovery and validation; survival analysis is a plus.
• Proven ability to work independently, prioritize tasks effectively, define next steps and manage multiple projects and stakeholders in a fast-paced environment.
• Excellent communication skills, with the ability to deliver complex scientific concepts to diverse audiences.
  Curiosity, creativity and a solution-oriented mindset when addressing scientific problems.
  Fluency in English (written and verbal).

The salary for this position is expected to range between $126,000 and $234,000 per year. 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.