Director Data Science

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

Job Description

200+ compounds are supported by the quantitative drug developers in Early Development Analytics at Novartis. We transform data from multiple sources - clinical, biomarker, digital sensor, imaging - into analyses and insights that build the basis for making innovative drugs accessible for patients. We influence decision-making in cross-functional international teams from early to late phase drug development.

The Early Development Analytics group is searching for a Director/Sr Director Data Scientist. In this role, you will drive the biomarker strategy for early and late development clinical programs in multiple indications or disease areas, working closely with interdisciplinary teams to analyze and interpret biomarker data to inform critical project decisions and understand mechanisms of response/resistance to therapy. You will be responsible for designing and executing the biomarker strategy in those programs to inform drug development, and set the strategy for addressing biomarker issues in early/late phase trials, regulatory submissions and directly influence drug development decisions with internal and external partners.

Your responsibilities will include;

• In collaboration with cross-functional quantitative partners, provide quantitative, scientific and strategic input to support the execution of the integrated precision medicine biomarker strategies in drug development.
• Contribute to planning, execution, interpretation, and communication of innovative exploratory biomarker analyses, to facilitate internal decision making, publications and support submissions
• Represent the Analytics line functions on cross-functional teams for the assigned projects. Responsible for functional alignment and ensuring line function awareness throughout the assigned activities
• Independently lead interactions with external parties (e.g., key opinion leaders, health authorities), and represent Novartis in statistical discussions at external congresses, conferences and scientific meetings
• Drive and promote the use of innovative approaches within the organization, through scientific collaborations, publications in scientific peer reviewed journals and presentations at professional meetings
• Lead or support key departmental or cross-organizational initiatives (e.g., infrastructure/ process-related or scientific activities)
• Contribute to the scientific content of materials for internal decision boards/regulatory/submission documents: Briefing Books, decision criteria, trial design(s), responses to Health Authority questions.
• Collaborate with other line functions. Explain statistical concepts in an easily understandable way to non-statisticians and provide adequate statistical justifications and interpretation of analysis results for actions/decisions/statements, when required.
• Develop and mentor junior data scientists. As global manager, responsible for recruitment, retention, and professional development of up to 10 data scientists.

May serve as:

• Global manager of a small team
• Individual contributor who is a thought leader in drug development biostatistics across related indications/areas
• Diversity & Inclusion / EEO
• Novartis is committed to building an outstanding, inclusive work environment and diverse teams representative of the patients and communities we serve.

Minimum Requirements

What you’ll bring to the role

• PhD or MS in statistics, data science, bioinformatics, or other quantitative field
• 8+ years of extensive practical experience and track record of implementing advanced quantitative methods in omics/multi-omics data analysis to influence decision making and deliver value/business impact. Position will be Director/Senior Director, level will commensurate with experience.
• Strong knowledge and understanding of statistical methods such as meta-analysis, mixed effect modeling, longitudinal modeling, time to event analysis, Bayesian methods, bagging/boosting, variable selection methods (e.g., lasso, elastic net, random forest), design of experiments
• Strong programming skills in R. Demonstrated knowledge of data visualization and exploratory analysis.
• Considerable leadership and people management experience with a focus on coaching, mentoring, career development, and creating a team environment of trust and collaboration
• Extensive knowledge of drug development processes
• Excellent interpersonal and communication skills (verbal and writing), demonstrated experience working effectively on a multidisciplinary team in a matrix organization

• Desirable:
• Good understanding of clinical study design principles and familiarity working with clinical data in a clinical trial setting
• Experience with high dimensional exploratory biomarker platforms (e.g., next generation sequencing, transcriptomics, proteomics, flow cytometry, etc.)
• Working knowledge of Python, with expertise in big data, web-based applications, good coding practice, source code management (Git, bitbucket)