Full Stack Senior Data Scientist

Full Stack Senior Data Scientist at Cardinal Health in Boise, Idaho, United States Job Description Fuse is on a mission to disrupt healthcare. Our focus on technology, design and a product mindset will help drive that disruption and establish Cardinal Health as a leader in healthcare technology. Fuse's innovation culture and modern product development teams power the evolution of our commercial products and spark the creation of new businesses and products. We leverage technology and insights across the enterprise to solve customer problems and forge new models. Design thinking drives our teams to imagine and invent the next horizon. It's more than technology innovation - it's creating new business models beyond our wildest dreams. With a strong leadership team setting the bar high, Fusers are challenged to bring their creativity, technical expertise and diverse perspectives to do the best work of their lives. The Full Stack Senior Data Scientist is a key role in the transformation of business. They will work closely with business stakeholders to understand their goals and determine how data science can be used to achieve those goals. They will use relevant statistical techniques, machine learning models and artificial intelligence algorithms to analyze data, design data models and derive insights to influence actions that maximize business value and effectiveness for the commercial technology segments. Responsibilities Data Engineering + Experience in building end-to-end ML pipelines from data ingestion, feature engineering, model training, deploying and scaling the model in production + Experience in model training, model optimization, ML system architecture design, and scalable ML model deployment + Build large-scale batch and real-time data pipelines with data processing frameworks like Scio, Google Cloud Platform and the Apache Beam + Proficiency in Python and relevant libraries for machine learning such as scikit-learn and Pandas, as well as Jupyter Notebooks. + Experience in building solutions for AI/ML services and platforms with models in production, ML Ops, CI/CD automation of ML pipelines in a cloud-based environment e.g., (GCP) + Experience interacting with REST APIs and microservices + Familiarity with containerization technologies (e.g., Docker) and orchestration tools (e.g., Kubernetes) for scalable and efficient model deployment. Data Science/Machine Learning + Designing and developing machine learning and deep learning solutions and systems. + Using statistical analysis to determine data modeling?approach, train To view full details and how to apply, please login or create a Job Seeker account