Responsibilities

• Research, evaluate, and implement artificial intelligence algorithms. Ensure projects are delivered in-line with reference architecture, road map and to the defined standards and best practices. Troubleshoot technical issues within ML platforms.


• Diagnose business needs, analyze business processes, data flows, IT / technical artifacts and extract understanding of how the system or business process works as input for model development.


• Identify high-value ML business opportunities and work with Business and IT stakeholders to realize business benefit.


• Use deep subject matter/ functional expertise, influence and process skills to help internal/external customers and stakeholders identify and meet their high priority needs while considering cultural and diversity implications.


• Work across diverse teams, perspectives and opinions and quickly build consensus.


• Encourage informed risk-taking and act as a catalyst for innovation at Cardinal Health


• Proactively develop, maintain and evangelize technical knowledge in Machine Learning and adjacent technologies. 

Core Capabilities:

• Possess deep functional and technical understanding of the Machine Learning technologies (Google’s Cloud Platform, custom and COTS-embedded) and leverage it across Cardinal Health’s large, complex and diverse landscape.


• Business acumen (strong understanding of how business operates, and how to harness data and analytics to meet business needs)


• Ability to develop and deploy advanced analytical models and algorithms that drive profitable growth, predictable patterns and areas of opportunity.


• Maintain a solid understanding of up and downstream impacts implementing solutions using ML technologies.


• Engage early in project efforts in order to analyze current solutions, provide solution options and recommendations, understand business process impact, provide accurate estimates.


• Aide adoption of ML solutions within the business by conducting training, coordinating demos.


• Establish development and delivery best practices in order for ML implementations to minimize rework and maintenance cost. Build ML architectures that work at Cardinal Health scale.

Qualifications

Required:

• 7+ years in the distribution or Healthcare industry and deep knowledge of their business practices.


• 3+ years of proven Machine Learning experience and involvement in packaged platform delivery and management.


• Strong working knowledge of a variety of machine learning techniques (Regression, Clustering, Decision Tree, Probability Networks, Neural Networks, Bayesian models etc.)


• Experience with Machine Learning and related technologies such as Python, Tensorflow, Torch, Amazon SageMaker, Jupiter Notebooks.


• Understanding of cloud data engineering and integration concepts.

Preferred:

• Delivery experience with Google Cloud Platform.


• Delivery of related information software solutions such as data warehouses and integration platforms.


• Agile development skills and experience.