Team Leader in Data Science, Disease Area X
Novartis
September 04, 2026
Remote friendly (Cambridge, MA)
United States
IT
Key Responsibilities:
- Lead data science strategy and execution for hypothesis-driven discovery programs (study design, experiment analysis, interpretation of complex biological datasets).
- Drive multi-omics analytics across genomics, transcriptomics, proteomics, single-cell, spatial, imaging, and clinical data to support target and biomarker portfolios.
- Translate scientific questions into computational strategies using appropriate statistical/ML/AI and bioinformatics approaches.
- Operationalize responsible use of generative and/or agentic AI in drug discovery workflows with scientific rigor, data governance, and human oversight.
- Contribute hands-on work in scientific software development, data engineering, workflow automation, reproducible analysis, and scalable pipelines.
- Partner cross-functionally to shape experimental design and accelerate decision-making.
- Prioritize resources across projects to balance strategic impact and delivery timelines.
- Lead, coach, and develop direct reports; build a collaborative, inclusive, high-performing team.
- Communicate findings and recommendations via presentations, governance, publications/posters, and external forums.
- Promote FAIR data practices, reproducible research, high-quality documentation, tracking, and scalable standards.
Essential Requirements:
- PhD (preferred) in a quantitative/life science field (e.g., Data Science, Computational Biology/Bioinformatics, Molecular Biology, Genetics, Engineering).
- 6+ years applying computational biology/bioinformatics, AI/ML, statistics, or data science to drug discovery/translational research.
- Experience leading/managing data scientists in matrix environments with internal and external collaborators.
- Demonstrated ability to lead analyses using multi-omics/translational datasets (e.g., RNA-seq, single-cell RNA-seq, proteomics, genomics, spatial biology, imaging).
- Practical software development and reproducible workflows; Python and/or R; GitHub, HuggingFace, workflow managers, Jupyter notebooks, containers.
- Cloud/enterprise-scale compute and HPC experience.
- Familiarity with modern AI/ML (including generative/agentic AI).
- Experience acquiring/curating/engineering datasets with data governance, privacy, and security.
- Ability to shape strategy cross-functionally and translate results into portfolio decisions.
- Track record of scientific impact (publications, presentations, decision support/portfolio contributions).
- Strong communication, interpersonal skills, ethical judgment, resilience, and self-awareness.
Compensation & Benefits:
- Salary expected ranges: $160,300–$297,700 (Senior Principal Scientist) or $176,400–$327,600 (Associate Director).
- Performance-based cash incentive; potential eligibility for annual equity awards (level-dependent).
- US eligible employees: comprehensive health/life/disability, 401(k) with match, and time off (vacation/personal/holidays/leave).
- Lead data science strategy and execution for hypothesis-driven discovery programs (study design, experiment analysis, interpretation of complex biological datasets).
- Drive multi-omics analytics across genomics, transcriptomics, proteomics, single-cell, spatial, imaging, and clinical data to support target and biomarker portfolios.
- Translate scientific questions into computational strategies using appropriate statistical/ML/AI and bioinformatics approaches.
- Operationalize responsible use of generative and/or agentic AI in drug discovery workflows with scientific rigor, data governance, and human oversight.
- Contribute hands-on work in scientific software development, data engineering, workflow automation, reproducible analysis, and scalable pipelines.
- Partner cross-functionally to shape experimental design and accelerate decision-making.
- Prioritize resources across projects to balance strategic impact and delivery timelines.
- Lead, coach, and develop direct reports; build a collaborative, inclusive, high-performing team.
- Communicate findings and recommendations via presentations, governance, publications/posters, and external forums.
- Promote FAIR data practices, reproducible research, high-quality documentation, tracking, and scalable standards.
Essential Requirements:
- PhD (preferred) in a quantitative/life science field (e.g., Data Science, Computational Biology/Bioinformatics, Molecular Biology, Genetics, Engineering).
- 6+ years applying computational biology/bioinformatics, AI/ML, statistics, or data science to drug discovery/translational research.
- Experience leading/managing data scientists in matrix environments with internal and external collaborators.
- Demonstrated ability to lead analyses using multi-omics/translational datasets (e.g., RNA-seq, single-cell RNA-seq, proteomics, genomics, spatial biology, imaging).
- Practical software development and reproducible workflows; Python and/or R; GitHub, HuggingFace, workflow managers, Jupyter notebooks, containers.
- Cloud/enterprise-scale compute and HPC experience.
- Familiarity with modern AI/ML (including generative/agentic AI).
- Experience acquiring/curating/engineering datasets with data governance, privacy, and security.
- Ability to shape strategy cross-functionally and translate results into portfolio decisions.
- Track record of scientific impact (publications, presentations, decision support/portfolio contributions).
- Strong communication, interpersonal skills, ethical judgment, resilience, and self-awareness.
Compensation & Benefits:
- Salary expected ranges: $160,300–$297,700 (Senior Principal Scientist) or $176,400–$327,600 (Associate Director).
- Performance-based cash incentive; potential eligibility for annual equity awards (level-dependent).
- US eligible employees: comprehensive health/life/disability, 401(k) with match, and time off (vacation/personal/holidays/leave).