Data Scientist/Machine Learning Specialist - MLOps, Data Science

Data Scientist/Machine Learning Specialist

Headquartered in Dublin, Ohio, Cardinal Health, Inc. (NYSE: CAH) is a global, integrated healthcare services and products company connecting patients, providers, payers, pharmacists and manufacturers for integrated care coordination and better patient management. Backed by nearly 100 years of experience, with more than 50,000 employees in nearly 60 countries, Cardinal Health ranks among the top 20 on the Fortune 500.

Department Overview

augmented Intelligence (augIntel) builds automation, analytics and artificial intelligence solutions that drive success for Cardinal Health by creating material savings, efficiencies and revenue growth opportunities. The team drives business innovation by leveraging emerging technologies and turning them into differentiating business capabilities.

Job Overview

Create and deliver business value at Cardinal Health by influencing and leading the charge of the machine leaning domain across business and IT. Work closely with business stakeholders to understand their goals and determine how data can be used to achieve those goals. Design and develop machine learning and deep learning solutions to maximize business value and effectiveness.

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 develop and deploy advanced analytical models and algorithms that drive profitable growth, predictable patterns and areas of opportunity.
• Aide adoption of ML solutions within the business by leveraging explainable techniques, conducting training, and 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.
• 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.

Desired Qualifications:

• 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.
• Prefer experience in Data Movement Technologies and Cloud Data Warehouse technologies including but not limited to experience with GCP, Big Query, Google Cloud Storage.
• Excellent oral and written communication skills
• Prefer experience with DevOps Agile practices

Candidates who are back-to-work, people with disabilities, without a college degree, and Veterans are encouraged to apply.

Cardinal Health supports an inclusive workplace that values diversity of thought, experience and background. We celebrate the power of our differences to create better solutions for our customers by ensuring employees can be their authentic selves each day. Cardinal Health is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, ancestry, age, physical or mental disability, sex, sexual orientation, gender identity/expression, pregnancy, veteran status, marital status, creed, status with regard to public assistance, genetic status or any other status protected by federal, state or local law.

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