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Young Innovations · 2 months ago

Senior Supply Chain Data Analyst

USA

Full-time

Onsite

Senior Level

5+ years exp

Young Innovations is a manufacturer and marketer of high-quality dental equipment. The Senior Supply Chain Data Analyst will lead the development and execution of advanced analytics and automation initiatives to support the Global Supply Chain Team, focusing on data infrastructure and proactive decision-making.

DentalMarketingSupply Chain Management

Responsibilities

Design, develop, and maintain analytics, dashboards, and AI-powered reports to support daily, weekly, and strategic supply chain execution — including supplier performance, materials availability, freight optimization, and inventory management

Use advanced analytics techniques (e.g., regression, time-series forecasting, optimization modeling, and machine learning) to identify trends, predict risks, and recommend corrective actions

Support the creation of executive presentations and communication materials to clearly convey insights, trends, and recommendations to leadership

Automate data workflows and pipelines across ERP, WMS, and TMS systems using SQL, Python, Power Automate, and cloud-based tools (e.g., Azure, Snowflake, or Databricks)

Develop and deploy machine learning and predictive analytics models to improve demand forecasting, supplier reliability, and logistics cost efficiency

Manage and optimize the Supply Chain SharePoint environment, ensuring effective integration across Microsoft 365 platforms and collaboration tools

Partner with IT and Finance to ensure accurate and timely ETL and data governance processes

Validate data integrity and enhance analytical data models and cubes

Ensure data accuracy, reliability, and transparency across analytics platforms

Identify and resolve data and reporting gaps, implementing corrective or preventive measures

Collaborate with Procurement, Planning/SIOP, Logistics, and Finance to identify opportunities for process automation, digital transformation, and continuous improvement

Manage multiple stakeholders and priorities effectively, delivering high-quality analysis within deadlines

Deliver timely and reliable reports and dashboards with actionable insights

Qualification

SQLPythonData AnalyticsMachine LearningPower BIERP SystemsData GovernancePredictive AnalyticsAPICS CertificationLean Six SigmaAnalytical ThinkingCommunication Skills

Required

Bachelor's degree in Analytics, Data Science, Supply Chain, Computer Science, Engineering, or Business with at least 5 years of relevant experience in analytics or supply chain management

Working knowledge of manufacturing and supply chain operations, including MRP, BOM, inventory management, and logistics principles

Strong technical proficiency with SQL (data querying and transformation)

Strong technical proficiency with Power BI or similar visualization tools

Strong technical proficiency with Python (pandas, scikit-learn, or similar libraries for analytics)

Strong technical proficiency with Microsoft 365 Suite, including SharePoint, Power Apps, and Power Automate

Experience with ERP systems (Oracle, SAP, or similar) and their underlying data structures

Ability to translate complex data into business insights and visual stories for leadership

Excellent problem-solving, analytical thinking, and communication skills

Ability to manage multiple complex projects simultaneously and deliver high-impact results

Preferred

Advanced degree (M.S. or MBA) with a concentration in Analytics, Supply Chain, or Operations Research

Certifications: APICS, CPIM, CSCP, Lean Six Sigma, or similar

Experience building predictive or prescriptive analytics models (e.g., demand forecasting, inventory optimization, lead time variability, anomaly detection)

Familiarity with cloud-based analytics environments (Azure Synapse, Snowflake, or Databricks)

Experience implementing AI-enabled solutions (forecasting automation, AI copilots, RPA) within supply chain or manufacturing environments

Knowledge of global supply chain regulations, trade compliance, and risk management