Responsibilities may include the following and other duties may be assigned: 

Execution: 

• Work independently and as a part of large teams to implement strategic imperatives and establish operational plans for multiple Global Ops programs. Recognized master in professional discipline 

• Analyze, quantify, and visualize large amounts of data from multiple disparate sources to generate verifiable conclusions  

• Develop, inspect, transform, mine, and model data to support business processes with statistical significance, forecasting, anomaly detection, decision trees, logistic regression, probabilities, etc. 

Productionization: 

• Manage all aspects of end-to-end analytics, model execution, data accuracy monitoring, drift monitoring, model re-training, utilizing customized report building functions of systems 

• Develop, configure, and maintain our machine learning infrastructure and pipelines, ensuring they are scalable, reliable, and secure. 

• Work closely with data scientists to operationalize machine learning models, including deployment, monitoring, and version control. 

• Implement automated processes for data validation, model training, model evaluation, and model deployment. 

• Optimize machine learning workflows for performance and efficiency. 

• Develop tools and frameworks to enable end-to-end automation of the machine learning lifecycle. 

• Monitor and analyze model performance and data quality and troubleshoot any issues that arise. 

Lead, Mentor, and Evangelize: 

• Partner with AI/ML practitioners inside and outside Medtronic to bring the latest best practices, tools, and techniques 

• Stay up to date with the latest technologies and practices in MLOps and incorporate them into our workflows as appropriate. 

• Communicate data stories and insights to the non-technical community, describe model outcomes to the technical team. Lead and mentor other data scientists on the team 

Required Knowledge and Experience: 

• Fluent in English (written and verbal) 

• Bachelor’s degree in science, engineering, or technical discipline required 

• Minimum of 3 years of relevant experience 

• Strong experience in machine learning, data engineering, and software development 

• Data query skills with SQL 

• Hands-on experience with building and productionizing AI/ML Models 

• Proficient in Python and R. Familiarity with machine learning frameworks 

• Expertise in setting up and maintaining Git for version control and deliverables management 

• Experience with DevOps tools (e.g., Docker, Kubernetes) and cloud services (AWS, Azure) 

• Expertise in BI tools (PowerBI, etc.) in a large-scale, complex business environment 

Nice to Have: 

• Expertise in AI/ML tools (Azure ML, Dataiku, etc.) 

• Understanding of ETL methodologies and tools (Informatica, etc.) 

• Experience working with Global Operations of large organizations, preferably in medical devices. 

• Ability to learn, lead, mentor, educate and support team members 

• Excellent understanding of data analytic and statistical tools, capable of explaining the underlying concepts and principles. 

• Experience working with large volumes of data from multiple operations functions 

• Proven leadership skills and business acumen; performance driven. Proven track record of taking ownership and driving results. 

• Excellent oral and written communications skills with the ability to interface and influence at all organizational levels. 

• Demonstrated ability in managing/supporting multiple projects in a deadline driven environment. 

• High level of initiative and passion to drive change.