Associate Director Data Science

Job Description Summary

Understands complex and critical business problems from a variety of stakeholders and business functions, formulate 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 definition, 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 be able 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 set strategy, manage budget, ensuring appropriate staffing and coordinating projects within the area supervised. If managing a team: empowers the team and provides guidance and coaching, with limited guidance from more senior managers.

Our Development Team is guided by our purpose: to reimagine medicine to improve and extend people's lives.

To do this, we are optimizing and strengthening our processes and ways of working.

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 an Associate Director Data Science 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.

• 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.

• Ph.D. in data science, biostatistics, or other quantitative field (or equivalent).
• Working 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 (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)
• Ability to develop and deliver clear and concise presentations for both internal and external meetings in key decision-making situations.

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