Senior Principal Data Scientist

Job Description Summary

Understand complex and critical business problems, formulate integrated analytical approaches to mine data sources, employ statistical methods and machine learning algorithms to contribute to solving unmet medical needs, discover actionable insights, and automate processes for reducing effort and time for repeated use. Manage the implementation and adherence to the overall data lifecycle of enterprise data from data acquisition or creation through enrichment, consumption, retention, and retirement, enabling the availability of useful, clean, and accurate data throughout its useful lifecycle. High agility to work across various business domains. Integrate business presentations, smart visualization tools, and contextual storytelling to translate findings back to business users with a clear impact. Independently manage budget, ensuring appropriate staffing and coordinating projects within the area.

Our Development Team is guided by our purpose: to reimagine medicine to improve and extend people's lives. We are optimizing and strengthening our processes and ways of working, investing in new technologies, and building specific therapeutic area and platform depth and capabilities to bring our medicines to patients even faster.

As a Senior Principal Data Scientist in the Medical Affairs Advanced Quantitative Sciences group, you will be responsible for the discussion and implementation of data science methodologies applied to patient-level data across clinical development. You will combine your data science and AI skills with your scientific knowledge in biology or medicine to enrich drug development decisions in close collaboration with internal and external partners.

This role offers hybrid working, requiring 3 days per week or 12 days per month in our London Office.

• Contribute to planning, execution, interpretation, validation, and communication of innovative exploratory analyses and algorithms to facilitate internal decision-making.
• Provide technical expertise in data science and predictive machine learning/AI to identify opportunities for influencing internal decision-making.
• Perform hands-on analysis of integrated data from clinical trials and the real world to generate fit-for-purpose evidence applied to decision-making in drug development programs.

• Ph.D. in data science, biostatistics, or other quantitative field (or equivalent).
• More than 3 years of experience in clinical drug development with extensive exposure to clinical trials.
• Strong knowledge and understanding of statistical methods such as time-to-event analysis, machine learning, meta-analysis, mixed-effect modeling, longitudinal modeling, Bayesian methods, variable selection methods.
• Strong programming skills in R and Python, with demonstrated knowledge of data visualization, exploratory analysis, and predictive modeling.
• Excellent interpersonal and communication skills (verbal and writing).

Novartis is committed to building an outstanding, inclusive work environment and diverse teams representative of the patients and communities we serve.

We are an equal opportunities employer and welcome applications from all qualified candidates.