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 103,000 colleagues serve people in more than 160 countries.
Primary Job Function
The Data Scientist will be responsible for working on complex problems in the field of life-saving implantable medical devices. He or she will use machine learning, artificial intelligence, statistical modeling, data mining, and visualization techniques to provide analytics solutions to a wide range of challenging projects. As a key member of the team, the candidate will develop solutions to curate and analyze large quantities of medical data. The candidate will work on projects that quantify real-world clinical and economic outcomes of life-saving therapies used in chronic disease states.
The candidate will collaborate effectively with internal stakeholders and cross-functional teams. He or she will present solutions and insights in concise and effective manner to technical and non-technical audiences. Candidate will work on a diverse team with scientists, engineers, and physicians on a variety of projects and act as a subject matter expert for data science. He or she will support preparation of scientific conference presentations and publications.
- Curate and analyze complex clinical data
- Design and execute data analyses for real-world evidence generation
- Perform integrative analyses of clinical and device data from large patient cohorts
- Translate real-world observations into clinical actionable insights using precision medicine, phenotyping, machine learning, artificial intelligence
- Apply scientific knowledge on data modeling, data analytics, predictive algorithms, and other data science principles to create concepts, develop prototypes, and generate insight from data
- Research and develop AI and Deep Learning algorithms
- Solve analytical problems and effectively communicate methodologies and results
- Draw inferences and conclusions
- Create dashboards and visualizations of processed data to identify trends
- Translate project needs and goals into a data driven analytical approach
- Understand the context of big data and its implications around privacy
- Work autonomously in a fast-paced environment
- Work with a broad range of technologists and support personnel both within and outside of Abbott
- PhD in quantitative discipline, such as computer science, engineering, data science, bioinformatics, statistics, mathematics, machine learning or related field.
- 1-2 years of work or internship experience.
- In-depth knowledge of contemporary machine learning, pattern recognition and data-mining techniques.
- Analytical skills with a solid foundation in programming (R, SAS, Python, SQL, NoSQL, PostgreSQL) and data/database design
- Strong oral and written communication skills
- Prior experience in R or SAS
- Proficient in data warehousing, data modeling, ETL and SQL
- Prior experience or working knowledge with one or more of the following tools and technologies: Spark, Clojure, Hive, Pig, Redshift
- Experience with big-data architecture, operating systems and tools for big-data analytics