Data Scientist

Data Scientist will execute data science projects to solve difficult, non-routine analysis problems by applying advanced methods to create a combination of solutions, new hypotheses based on both new and existing real-world data related to quality. By applying advanced methods including artificial intelligence, machine learning, causal inference, advanced statistics, natural language processing and other related techniques, this incumbent will be a key go to person to ask questions, connect the dots and uncover opportunities that lie hidden within data with the ultimate goal of realizing the data's full potential.

• Is responsible for developing and implementing the data models within the defined analytics framework, enabling global and regional Medicine functions to make data driven decisions related to quality.
• Manages and coordinates medium size/complexity projects to evaluate the impact of QM initiatives in the Medicine organization.
• Contributes to continuous improvement of the QM analytics framework according to industry standards.

Accountabilities

• Contribute to the delivery of successful business and customer focused quality data analytics solutions.
• Understand quality-related business problems and develop and optimize use cases for the data analytics framework.
• Understand data, IT, and business constraints.
• Investigate additional data sources to be used in predictive data analytics modeling.
• Generate and interpret data analytics outputs for quarterly Business Intelligence Reporting.
• Utilize high quality, cutting edge analytic approaches to solve problems and transform towards smart decision making: Apply strong expertise in data science to continuously optimize the QM data analytics models and use cases for quality-related data driven decision making.

Lead Data Science activities of Data Management Operations:

• Develop and maintain data operational processes adhering to all compliance requirements.
• Develop and maintain the monitoring process for data science models in production.
• Develop and implement processes for oversight of data collection/curation and data review.