Supply Chain Data Analyst

Mini-Circuits•Melville, NY

23h•$85,000 - $95,000

About The Position

Mini-Circuits designs, manufactures and distributes integrated circuits, modules, and sub-systems for high-performance radio frequency (RF) and microwave applications. With design, sales and manufacturing locations in over 30 countries, Mini-Circuits’ products are used in a range of wired and wireless communications applications. Our products are also used in detection, measurement and imaging applications, including military communication, guidance and electronic countermeasure systems, commercial, scientific, military land, sea and aircraft; automotive systems, medical systems, and industrial test equipment. Mini-Circuits’ sells its products to over 20,000 customers globally through our direct sales force, applications engineering staff, sales representatives, as well as through our extensive website. Position Summary: The Supply Chain Data Analyst plays a key role in supporting and improving supply chain operations through data-driven insights. This role develops and maintains reports and dashboards, analyzes supply chain performance, and supports decision-making across demand planning, inventory management, procurement, and production scheduling. The analyst ensures data integrity, identifies trends, and provides actionable insights to enhance operational efficiency, reduce costs, and improve service. Collaborating with teams across the organization, this role helps drive informed decisions that directly impact business performance.

Requirements

Bachelor’s degree required, Supply Chain Management, Data Analytics, or a related field preferred
5+ years of experience in data analytics, supply chain analysis, or manufacturing operations.
Proficient in Tableau, and advanced Excel (formulas, Power Query, macros).
Skilled in SQL for data extraction, transformation, and analysis.
Experience with ERP or MRP systems (SAP or equivalent).
Strong understanding of end-to-end supply chain processes
Demonstrated ability to build dashboards and reports to monitor performance and support decision-making.
Knowledge of supply chain principles such as demand forecasting, inventory optimization, and supplier performance.
Excellent organizational, communication, and collaboration skills in fast-paced environments.
Strong analytical, detail-oriented, and problem-solving skills.
Proactive and self-directed, with the ability to manage multiple priorities in a fast-paced environment.

Nice To Haves

APICS certification (CPIM, CSCP) preferred.
Knowledge of statistical analysis, data modeling, and forecasting methodologies.
Proficiency in interpreting and communicating complex data insights to non-technical stakeholders.

Responsibilities

Develop, manage, and maintain reports, dashboards, and KPIs to monitor supply chain performance (e.g., forecast accuracy, on-time delivery, inventory turns, capacity utilization).
Analyze large datasets across all supply chain functions to provide actionable insights, identify trends, and support data-driven decision-making.
Ensure data accuracy, integrity, and consistency across ERP, MRP, and planning systems.
Collaborate with cross-functional teams (Planning, Manufacturing, Finance, Operations) to identify reporting needs and implement process improvements.
Support demand forecasting, inventory optimization, and supplier performance analysis through data-driven insights.
Automate recurring reports and streamline data workflows using Tableau, SQL, or similar tools.
Provide ad hoc analyses and visualizations to support operational and executive decision-making.
Identify trends, risks, and performance gaps, recommending actions to improve efficiency, reduce costs, and enhance service levels.
Partner with IT and Data Engineering teams to enhance data pipelines, integrations, and reporting infrastructure.
Perform root cause analysis on forecast deviations, data anomalies, and operational bottlenecks, providing actionable recommendations.
Support the implementation of new analytics tools or system enhancements to improve accessibility of key performance metrics.