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.

     

JOB DESCRIPTION:

Working at Abbott

At Abbott, you can do work that matters, grow, and learn, care for yourself and family, be your true self and live a full life. You’ll also have access to:

• Career development with an international company where you can grow the career you dream of.

• Free medical coverage for employees* via the Health Investment Plan (HIP) PPO

• An excellent retirement savings plan with high employer contribution

• Tuition reimbursement, the Freedom 2 Save student debt program and FreeU education benefit - an affordable and convenient path to getting a bachelor’s degree.

• A company recognized as a great place to work in dozens of countries around the world and named one of the most admired companies in the world by Fortune.

• A company that is recognized as one of the best big companies to work for as well as a best place to work for diversity, working mothers, female executives, and scientists.

The Opportunity

As a Data Scientist, you will lead the analysis and interpretation of numerous data sources (interventional clinical trial datasets, observational human studies and real world evidence) from people with diabetes (PWDs). Results will inform feature sets for products to help PWDs better manage their diabetes.  

What You'll Work On

The ideal candidate will be one who can effectively analyze source data sets and translate those findings into actionable insights that can be understood by cross functional stakeholders.  More specifically, they will be expected to do the following:  develop standardized analysis methods and dashboards for certain common datasets as well as bespoke methods for unique datasets, define and test hypotheses for each dataset, generate summary documents of results with recommendations, and lead translation of these recommendations into real-life embodiments for testing.  The nature of this work is highly interdisciplinary, so the ideal candidate should value working with people from different professional backgrounds and be able to cultivate working cross-functional relationships.

              A strong working knowledge of the diabetes disease state (etiology, pathogenesis, progression and treatment) is highly preferred.  Such a knowledge will allow the incumbent to more effectively understand datasets, define hypotheses and draw actionable conclusions.

Responsibilities:

• Perform hypothesis-driven analysis of PWD user data from various sources (glucose monitors, medication delivery devices, activity trackers).

• Utilize findings from data analysis to formulate product features for next generation decision support tools.

• Effectively present findings and your own conclusions/recommendations to stakeholders of various backgrounds.  Requires the ability to aggregate and simplify results into memorable “take home” messages.

• Develop standardized analysis methods and visualization dashboards for certain commonly structured datasets as well as bespoke methods for unique datasets

• Define study endpoints, hypotheses and data analysis methods for human clinical trials.

• Participate in R&D initiatives to utilize time series data sets from multiple medical devices in the development of decision support algorithms for people with diabetes

• Assist system engineers in system-level characterization/verification of complex systems. 

• Communicate effectively with and participate on cross functional development teams with good negotiating skills to direct multi-disciplinary teams toward solutions.         

• Responsible for utilizing and maintaining the effectiveness of the quality system.

• Responsible for complian