Director Oncology Data Science LMW
Novartis
June 26, 2026
On-site
Cambridge, MA
$194,600 - $361,400 USD yearly
Clinical Research and Development
Key Responsibilities:
- Lead and develop a global team of US and Europe-based data scientists; drive high-quality data science grounded in deep biology and applicable data science methods.
- Co-develop and execute a data science strategy to advance innovation in low molecular weight (LMW) drug development.
- Align with Oncology Drug Development teams to embed LMW data science and ensure scientific direction.
- Interface with Oncology Disease Area leaders to align priorities and deploy resources.
- Collaborate with Oncology Data Science AI and other teams (e.g., generative chemistry) to develop and implement ML/AI algorithms, models, and platforms for predictive and prescriptive insights.
- Partner with IT, Chemistry, and Technology stakeholders; build shared projects.
- Contribute to Oncology Data Science leadership direction and represent the LMW portfolio.
- Collaborate with engineering teams to ensure data standards, data governance, data strategy, best practices, and reproducibility.
- Lead efforts in matrix teams (e.g., Translational Data Science Clusters; genomics/proteomics/spatial technologies).
- Present work in conferences, abstracts, and scientific journals.
Essential Requirements:
- Cambridge, MA onsite (no remote); 10% travel.
- Ph.D. in data science, computational biology, or related; strong understanding of biology, oncology, and LMW drug development.
- 10+ years in oncology drug development data science.
- Leadership: 5+ years people management in data science.
- QC and data analysis experience for assays such as bulk RNA-seq, scRNA-seq, and/or ChIP-seq/ATAC-seq/Hi-C.
- Expertise in quantitative/computational biology, AI/ML, and statistical modeling; track record delivering data-driven solutions.
- Excellent communication across cross-functional stakeholders.
- Publications and/or conference presentations.
Preferred Requirements:
- LMW-specific AI/ML (computational chemistry; generative AI in chemistry).
- Cell line profiling; shRNA/CRISPR screens; high-content imaging; proteomics; in vivo efficacy analysis.
Benefits (explicitly stated):
- Performance-based cash incentive; eligibility for annual equity awards (role-dependent).
- Comprehensive health, life, disability, and 401(k) with company contribution/match; time off (vacation, personal days, holidays, leaves).
Application instructions:
- Contact [email protected] or call +1(877)395-2339 for reasonable accommodation; include job requisition number.
- Lead and develop a global team of US and Europe-based data scientists; drive high-quality data science grounded in deep biology and applicable data science methods.
- Co-develop and execute a data science strategy to advance innovation in low molecular weight (LMW) drug development.
- Align with Oncology Drug Development teams to embed LMW data science and ensure scientific direction.
- Interface with Oncology Disease Area leaders to align priorities and deploy resources.
- Collaborate with Oncology Data Science AI and other teams (e.g., generative chemistry) to develop and implement ML/AI algorithms, models, and platforms for predictive and prescriptive insights.
- Partner with IT, Chemistry, and Technology stakeholders; build shared projects.
- Contribute to Oncology Data Science leadership direction and represent the LMW portfolio.
- Collaborate with engineering teams to ensure data standards, data governance, data strategy, best practices, and reproducibility.
- Lead efforts in matrix teams (e.g., Translational Data Science Clusters; genomics/proteomics/spatial technologies).
- Present work in conferences, abstracts, and scientific journals.
Essential Requirements:
- Cambridge, MA onsite (no remote); 10% travel.
- Ph.D. in data science, computational biology, or related; strong understanding of biology, oncology, and LMW drug development.
- 10+ years in oncology drug development data science.
- Leadership: 5+ years people management in data science.
- QC and data analysis experience for assays such as bulk RNA-seq, scRNA-seq, and/or ChIP-seq/ATAC-seq/Hi-C.
- Expertise in quantitative/computational biology, AI/ML, and statistical modeling; track record delivering data-driven solutions.
- Excellent communication across cross-functional stakeholders.
- Publications and/or conference presentations.
Preferred Requirements:
- LMW-specific AI/ML (computational chemistry; generative AI in chemistry).
- Cell line profiling; shRNA/CRISPR screens; high-content imaging; proteomics; in vivo efficacy analysis.
Benefits (explicitly stated):
- Performance-based cash incentive; eligibility for annual equity awards (role-dependent).
- Comprehensive health, life, disability, and 401(k) with company contribution/match; time off (vacation, personal days, holidays, leaves).
Application instructions:
- Contact [email protected] or call +1(877)395-2339 for reasonable accommodation; include job requisition number.