Commercial Artificial Intelligence Engineer

at  Abbott Laboratories

ABOUT ABBOTT

Abbott is a global healthcare leader, creating breakthrough science to improve people’s health. We’re always looking towards the future, anticipating changes in medical science and technology.
We’re empowering smarter medical and economic decision making to help transform the way people manage their health at all stages of life. Every day, more than 10 million tests are run on Abbott’s diagnostics instruments, providing lab results for millions of people.
Our rapid diagnostics solutions are helping address some of the world’s greatest healthcare challenges.

REQUIRED QUALIFICATIONS:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field.
• Proven experience in AI engineering, machine learning, and data engineering, preferably in the pharmaceutical or healthcare industry.
• Proficiency in programming languages such as Python, R, or Scala, as well as libraries and frameworks for AI development (e.g., TensorFlow, PyTorch, scikit-learn).
• Strong understanding of data management, data preprocessing, and feature engineering techniques.
• Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and big data technologies (e.g., Hadoop, Spark) is a plus.
• Excellent problem-solving skills, with the ability to analyze complex datasets and develop innovative solutions.
• Effective communication and collaboration skills, with the ability to work in multidisciplinary teams and influence decision-making processes.
  Follow your career aspirations to Abbott for diverse opportunities with a company that can help you build your future and live your best life. Abbott is an Equal Opportunity Employer, committed to employee diversity.
  Connect with us at www.abbott.com, on Facebook at www.facebook.com/Abbott and on Twitter @AbbottNews and @AbbottGlobal

• AI Solution Development:
• Design, develop, and deploy AI-driven solutions to enhance commercial operations, including sales forecasting, customer segmentation, and marketing campaign optimization.
• Utilize machine learning algorithms, natural language processing (NLP), and computer vision techniques to extract insights from diverse data sources.
• Data Engineering and Integration:
• Architect and implement scalable data pipelines to ingest, preprocess, and analyze large volumes of structured and unstructured data.
• Integrate AI models with existing systems and databases, ensuring seamless data flow and interoperability across platforms.
• Model Training and Evaluation:
• Train, validate, and optimize machine learning models using advanced algorithms and techniques.
• Evaluate model performance and iterate on algorithms to improve accuracy, robustness, and interpretability.
• Deployment and Monitoring:
• Deploy AI models into production environments, monitoring performance and ensuring reliability, scalability, and security.
• Implement mechanisms for continuous monitoring, model retraining, and feedback loop optimization to maintain model efficacy over time.
• Cross-functional Collaboration:
• Collaborate with sales, marketing, IT, and data science teams to understand business requirements and translate them into technical solutions.
• Serve as a subject matter expert on AI technologies, providing guidance and support to stakeholders across the organization.
• Compliance and IT Policy Adherence:
• Ensure that all AI solutions developed and deployed adhere to regulatory compliance standards and company IT policies.
• Collaborate with compliance and IT teams to conduct risk assessments and ensure that AI implementations meet security, privacy, and ethical guidelines.
• Implement controls and safeguards to protect sensitive data and mitigate potential risks associated with AI usage in commercial operations.