Data Scientist (Machine Learning And Ai)

Understand complex and critical business problems, formulates integrated analytical approach to mine data sources, employ statistical methods and machine learning algorithms to contribute solving unmet medical needs, discover actionable insights and automate process for reducing effort and time for repeated use. To 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. Independently manage budget, ensuring appropriate staffing and coordinating projects within the area. We are investing in new technologies and building specific therapeutic area and platform depth and capabilities – all to bring our medicines to patients even faster. We are seeking key talent, like you, to join us and help give people with disease and their families a brighter future to look forward to. 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 (including various clinical, real-world, and biomarker data) across clinical development. You will combine your data science and AI skills and 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. You will contribute to planning, execution, interpretation, validation and communication of innovative exploratory analyses and algorithms, to facilitate internal decision making. # You will provide technical expertise in data science and (predictive) machine learning/AI to identify opportunities for influencing internal decision making as well as discussions on white papers/regulatory policy. # You will perform hands-on analysis of integrated data from clinical trials and the real world to generate fit-for-purpose evidence that is applied to decision making in drug development programs. D. in data science, biostatistics, or other quantitative field (or equivalent). # 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 (e.G., lasso, elastic net, random forest), design of clinical trials. # Strong programming skills in R and Python. Demonstrated knowledge of data visualization, exploratory analysis, and predictive modeling. # Excellent interpersonal and communication skills (verbal and writing). # Why Novartis: Helping people with disease and their families takes more than innovative science. It takes a community of smart, passionate people like you. Commitment to Diversity & Inclusion: Novartis is committed to building an outstanding, inclusive work environment and diverse teams' representative of the patients and communities we serve. #