Over 200 discovery programs in 7 disease areas for a global team of scientists to focus on new molecular entities, with many opportunities for innovative data science. This is part of what makes Novartis the premier place to develop your career as a pharmaceutical professional. If you are curious, scientifically minded, and want to positively impact society by speeding delivery of novel therapies to patients with data then look no further, NIBR is the place to be. As a member of the PK Sciences Modeling & Simulation and Data Science group, you will have the opportunity to make a difference. If you have a collaborative nature, a commitment to teamwork, and a relentless focus on improving patient care, we want you to apply.

The Data Science group within PK Sciences is looking for a Data Engineer, Senior Expert I, to use your data engineering and programming skills to build systems that collect, manage and convert raw data into usable information for our scientists. We are seeking a curious, collaborative and proactive data engineer to contribute to the design, development and application of PK Science specific software applications to capture and visualize our data. Our group is growing, and we hope you will join us.

Your responsibilities include, but are not limited to:

• working towards real time availability of data for translational modelers and PK scientists.
• Eliminate bottlenecks like manual interventions and data reconciliations.
• Engage in process optimization, help consolidate existing and new data flows (FAIRplay for data ingestion, integration and analysis) to enable to respond to PK Science data-centric question rapidly.
• conducting one-off complex data analysis and visualizations
• being a liaison between partners involved: internal and external partners producing data, scientific teams having data intensive needs, NIBR teams designing enterprise solutions
• maintaining and growing your expertise in best practices for data handling especially as it applies to “big data” - FAIR data, data warehousing, data integration, archiving, scalable analysis solutions and visualization