Staff 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:

This position is open to our Chicago, IL, location in the Medical Devices Digital Solutions organization. Abbott Medical Devices, with revenue of >$16.5B in 2023, is a global leader in providing life-changing technology for the management and treatment of people living with chronic conditions, including Diabetes, Cardiovascular disease, Chronic Pain, and Movement Disorders.

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 Staff Data Scientist, Digital Solutions, reports to the Senior Manager of AI product Development, Digital Solutions. The Staff Data Scientist role will closely work with cross-functional product teams and responsible for designing, developing, and deploying external customer focused Product focused AI (PAI) / data science solutions to extract valuable insights and intelligence from large and complex medical datasets. The Staff Data Scientist role will exhibit a sense of inquisitiveness and a creative mind to uncover novel opportunities that will directly contribute to enhancing the quality of patient care and the development of innovative medical devices and therapy solutions.

WHAT YOU’LL DO

• As a Staff Data Scientist, your responsibilities will include conducting exploratory data analysis to identify patterns and trends and informing the development of robust algorithms.
• Design, develop, and optimize predictive models using machine learning to solve complex (clustering, classification, regression, simulation, and optimization) problems on large-scale data sets, ultimately optimizing and increasing clinical outcomes.
• Monitor and track model performance, identify and address issues, and iterate on models for continuous improvement.
• Perform rigorous testing and validation of models to ensure reliability and accuracy in diverse real-world scenarios.
• Build and maintain machine learning pipelines, including data ingestion, feature engineering, model training, and deployment.
• Create and maintain technical specifications and relevant documentation required to operate in a regulated medical device space.
• Work closely with cross-functional technical and non-technical stakeholders and teams to understand the complexity of the (business / clinical) domain, explain the application of complex machine learning concepts, and translate them into technical solutions.
• Collaborate with external partners, academic institutions, and healthcare providers to access additional data sources and research opportunities.
• Stay current with the latest advancements in machine learning research and implement relevant technologies to deliver state-of-the-art data science solutions.

EDUCATION AND EXPERIENCE YOU’LL BRING

Required:

• Master’s Degree in Data Science, Computer Science, Statistics, or a related field
• 4-6 years of experience in a relevant industrial or academic setting.
• Experience in the Life Science Industry.
• Proven expertise in data science methodologies and statistical techniques.
• Strong kn