Position Summary:
As a
Senior Data Analyst – Operations & Supply Chain
, you will be a key contributor in driving supply chain agility, operational excellence, and cost efficiency through data. This role sits at the intersection of analytics, business operations, and strategy, supporting teams across
manufacturing, planning, inventory management, and fulfillment.
You will develop scalable analytics tools and provide actionable insights that directly influence decision-making, with a focus on areas such as
inventory optimization, demand forecasting, MRP alignment, and capacity planning.
You will work cross-functionally with business leaders, stakeholders, and technical teams to build scalable analytics solutions that optimize our supply chain and operational processes.
Key Responsibilities:
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Develop Advanced Analytics Solutions:
Build and maintain dashboards and tools using Power BI, SQL, and Excel to deliver end-to-end visibility across supply chain KPIs including inventory turns, forecast accuracy, OTD, and production throughput.
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Supply Chain & Manufacturing Analysis:
Analyze complex datasets from ERP/MRP systems, demand plans, and production schedules to uncover inefficiencies, delays, and root causes. Drive continuous improvement in areas such as order flow, raw material availability, safety stock, and build plans.
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Inventory Planning & Forecasting:
Support demand and supply planning by building models that improve inventory health, predict shortages or overages, and align stock levels with customer demand and production constraints.
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MRP System Integration:
Partner with planning and operations teams to ensure data models and recommendations align with MRP logic and master data structures. Help shape BOM, lead time, and lot size assumptions to improve planning accuracy.
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Strategic Insights & Decision Support:
Translate data into strategic recommendations for operations and supply chain leaders. Focus on balancing service levels, working capital, and operational cost through better planning and scenario modeling.
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Automation & Scalability:
Design and implement automated pipelines, workflows, and reporting processes that reduce manual work, increase visibility, and enable proactive response to supply/demand variability.
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Stakeholder Engagement:
Act as a thought partner to manufacturing, logistics, and finance stakeholders. Communicate findings clearly and tailor insights to operational, technical, and executive audiences.
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Mentorship & Collaboration:
Provide guidance to junior analysts and support a culture of data fluency across the supply chain team.
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Project Leadership:
Lead and manage high-impact analytics initiatives, ensuring timely delivery and alignment with organizational goals.
Required Qualifications:
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Bachelor’s degree in Supply Chain, Finance, Accounting, Operations, Business Analytics, Industrial Engineering, or related field
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6–8 years of experience in data analytics with a strong focus on supply chain, operations, or manufacturing
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Advanced proficiency in
Power BI, SQL, and Excel
, with experience in automation and scripting
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Proven experience with
inventory planning, demand forecasting, MRP, ERP systems
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Experience with
predictive modeling, regression analysis, and correlation techniques
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Ability to distinguish signal from noise in complex datasets, providing clear insights for leadership
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Proven track record of
developing scalable, long-term analytical solutions
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Strong
project management skills
with the ability to lead and execute initiatives
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Strong
business acumen
and understanding of how supply chain data impacts cost, service, and capacity
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Strong understanding of financial and operational metrics and how they influence business performance
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Clear and confident communication skills, including stakeholder-facing presentations
Preferred Qualifications:
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Experience working with
Salesforce, Smartsheet, or other business intelligence tools
is a plus
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Experience building dashboards and tools that drive operational execution and planning decisions
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Experience in a
warehouse
,
manufacturing or production environment
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Familiarity with
production scheduling, capacity planning, and BOM structures
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Statistical or ML modeling experience for forecast or simulation
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Knowledge of Lean, Six Sigma, or process improvement methodologies
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Experience working with cross-functional data (e.g., sales, finance, operations) to enable full-picture decision-making