Global Supply Chain Insights Analyst

ResMed

United States

Remote

USD 73,000 - 109,000

Full time

14 days+

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Job summary

ResMed is seeking a Data Analyst to enable data-driven decisions across its Global Distribution, Logistics & Trade organization. You will transform complex data into actionable insights, partner with regional teams, and develop dashboards using Tableau/Power BI to support operational excellence.

The role requires 3+ years in data analytics, strong SQL, and AI literacy, with global collaboration across time zones.

Qualifications

Bachelor’s degree in data Analytics, Business Analytics, Supply Chain, Engineering, Statistics, Computer Science, or a related discipline.
3+ years of experience in data analytics, business intelligence, operations analytics, supply chain analytics, or a related field.
Strong SQL skills with experience querying and analyzing large datasets.
Experience building dashboards and reporting solutions using Tableau and/or Power BI.
Demonstrated AI literacy, including the ability to effectively use AI-powered tools to enhance data analysis, reporting, problem solving, productivity, and decision making.
Advanced Microsoft Excel skills.
Strong analytical, problem-solving, and critical-thinking abilities.
Ability to translate business questions into analytical solutions and actionable insights.
Excellent communication and presentation skills.
Strong organizational and prioritization abilities with the capability to manage multiple priorities.
Ability to work independently and effectively within a global, cross-functional environment.
Willingness and flexibility to support stakeholders across global time zones, including occasional participation in meetings outside traditional local business hours when required.

Responsibilities

Partner with global supply chain stakeholders to translate needs into analytical solutions.
Develop dashboards, reports, and KPI reporting using Tableau and/or Power BI.
Write SQL queries to extract, transform, and analyze data from enterprise systems.
Automate recurring reports and analytical workflows to improve efficiency and reduce manual effort.
Collaborate with Data Engineering and Technology teams to ensure data quality, consistency, and governance.
Maintain trusted KPI definitions, reporting standards, and business documentation.
Support self-service analytics capabilities that enable business users to access timely and reliable information.