Principal Data Scientist

Abbott is a global healthcare leader that helps people live more fully at all stages of life. Our portfolio of life-changing technologies spans the spectrum of healthcare, with leading businesses and products in diagnostics, medical devices, nutritionals and branded generic medicines. Our 114,000 colleagues serve people in more than 160 countries.

The Opportunity

Our Principal Data Scientist will work out of our Alameda, California location. This individual works as an integral part of a collaborative data and analytics team and responsible for analyzing real-world data to generate insights and develop machine learning models that drive the development and optimization of devices in Abbott Diabetes Care. The role requires drawing insights, and presenting results in a cohesive, intuitive, and simple manner to the functional stakeholders utilizing technologies to collect, clean, analyze, predict, and effectively communicate insights. Key functional stakeholders include research & development, clinical, medical, regulatory and market access teams.

What You Will Do

• Analyze large real-world datasets including device data, electronic health records (EHR), claims data, labs, and patient registries.
• Lead the design and execution of RWE studies including but not limited to:
• Treatment optimization and understanding treatment patterns
• Comparative effectiveness analyses
• Drug and device utilization
• Natural history and burden of disease
• Healthcare resource utilization
• Define and develop research strategy in line with business goals and guide the execution of the work across the team
• Collaborate with clinical, medical, regulatory, product managers and market access teams to integrate RWE into product development and lifecycle management.
• Execute key studies autonomously including but not limited to:
• Conduct advanced statistical analyses to determine trends and significant data relationships using techniques such as regression, time-series forecasting, clustering, decision trees, simulation, and scenario modeling.
• Develop and validate machine learning models and algorithms to apply predictive analytics to future data.
• Utilize technologies to collect, clean, analyze, and effectively communicate insights, including model logic and limitations.
  
  

Qualifications

• Bachelor’s Degree in Computer Science, Data Analytics or similar discipline including Mathematics, Statistics, Physics, or Engineering is preferred
• Advanced degree in Life or Physical Science, Bioengineering, Biostatistics, Biomedical Engineering, Epidemiology or closely related discipline is preferred
• Minimum 8 years work related experience with degree or sufficient transferable experience to demonstrate functional equivalence to a degree
• Advanced Experience with programming scripts such as Python, Java, Scala, C++ in Linux/Unix, and R
• Experience in applying data analysis techniques to a large set of data using big data systems such as Hadoop, Spark, MongoDB, or similar software
  
  

The base pay for this position is $128,000.00 – $256,000.00. In specific locations, the pay range may vary from the range posted.