Cardinal Health's Data & Analytics Function aims to leverage advanced analytics, machine learning, and optimization techniques to solve complex challenges within the Major Rugby business unit, focusing on demand forecasting, inventory optimization, logistics efficiency, and risk mitigation to uncover insights and drive meaningful deliverables for improved decision-making and business outcomes.
Requirements
- Strong programming skills in Python and SQL
- Proficiency in data visualization tools such as Tableau, or Looker, with a proven ability to translate complex data into clear, actionable business insights
- Deep understanding of machine learning, statistical modeling, predictive analytics, and optimization techniques
- Experience with cloud platforms (e.g., AWS, Azure, GCP) and big data technologies (e.g., Spark, Hadoop) is highly desirable
- Experience in Supervised and Unsupervised Machine Learning including Classification, Forecasting, Anomaly Detection, Pattern Detection, Text Mining, using variety of techniques such as Decision trees, Time Series Analysis, Bagging and Boosting algorithms, Neural Networks, Deep Learning and Natural Language processing (NLP).
- Experience with PyTorch or other deep learning frameworks
- Strong understanding of RESTful APIs and / or data streaming a big plus
Responsibilities
- Leads the design, development, and deployment of advanced analytics and machine learning models to solve complex business problems
- Develops and maintains scalable data science solutions, ensuring reproducibility, performance, and maintainability
- Evaluates and implements new tools, frameworks, and methodologies to enhance the data science toolkit
- Drives experimentation and A/B testing strategies to optimize business outcomes
- Ensures data quality, governance, and compliance with organizational and regulatory standards
- Stays current with industry trends, emerging technologies, and best practices in data science and AI
- Contributes to the development of internal knowledge bases, documentation, and training materials
Other
- 8–12 years of experience in data science, analytics, or a related field (preferred)
- Advanced degree (Master’s or Ph.D.) in Data Science, Computer Science, Engineering, Operations Research, Statistics, or a related discipline preferred
- Excellent communication and storytelling skills, with the ability to influence stakeholders and present findings to both technical and non-technical audiences
- Experience with product discovery and design thinking
- Experience with supply chain analytics is preferred
