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 109,000 colleagues serve people in more than 160 countries.
AQR Data Scientist
As a Data Scientist to join the Abbott Quality and Regulatory (AQR) division, you will provide high quality support for advanced analytics projects. You will develop advanced algorithms and models to generate key insights for multiple Abbott divisions. In addition, you will support the Quality Management Review process by automating periodic reports, streamlining data collection, and enhancing the efficiency of current business processes.
- Under the direction of the Data Science Manager, develop and lead advanced analytics projects and issue regular status/progress reports.
- Utilize technologies to analyze data, draw insights, and present results in a cohesive, intuitive, and simplistic manner to the non-technical audiences.
- Collect, compile and analyze data from multiple sources. Understand how to verify data accuracy and test for data integrity.
- Synthesize data projects into actionable items to improve business performance.
- Design and implement advanced modeling techniques such as classification, regression, and deep learning to address technical and business issues.
- Proactively think and ideate to facilitate ongoing, open dialogue where information and ideas are shared to generate solutions.
- Support quality management review, including data gathering, analysis and trending and preparing graphs.
- Strong analytical and technical skills
- Strong attention to detail
- Excellent verbal/written communication, user interaction & interpersonal skills
- Team player
- Data analytics experience and AI/ML modeling experience in Python or R
- Strong programming/scripting skill in Python or R
- Experience with the following concepts: NLP, Deep Learning, traditional supervised and unsupervised learning methods
- Data mining and data engineering experience (SQL, NoSQL, Spark, etc.)
- Dashboarding experience (Power BI, Tableau, etc.)
- Experience presenting complex data analysis to technical and non-technical stakeholders
- Quality and/or compliance experience is desired, but not a requirement.
- Familiarity and understanding with AWS cloud platform, Redshift, and SageMaker.
- Bachelor’s degree in engineering/science with 2 years of industry experience in data analytics/science.