Responsibilities:

• Collect and interpret supply chain data across Demand & Supply Planning, logistics, inventory, warehousing, and distribution.

• Analyze data trends to identify opportunities for process improvement, cost savings, and risk reduction.

• Monitor key performance indicators (KPIs) and develop dashboards and reports to track performance.

• Use data to model scenarios for inventory optimization, demand & supply planning, and supply chain performance.

• Assist in capacity planning and forecasting, using data models to recommend adjustments in supply or demand.

• Conduct root cause analysis for supply chain disruptions and develop actionable insights to mitigate risks.

• Prepare reports and visualizations that communicate complex data insights to supply chain and cross-functional teams.

• Present findings to stakeholders and recommend solutions based on data analysis.

• Automate data processes and reporting using modern data tools.

• Collaborate with cross-functional teams (Sales Ops, supply planning, logistics, production, finance, etc.) to align data-driven insights with business strategies.

• Partner with IT to ensure data quality, system integration, and the implementation of data governance protocols.

• Identify and implement data-driven solutions that increase efficiency and reduce costs.

• Stay updated on the latest trends and technologies in data analytics and supply chain management, suggesting improvements to current processes and systems.
  
  

Qualifications:

• Bachelor's degree in Supply Chain Management, Data Science, Operations Research, Mathematics, Statistics, Computer Science, or a related field. A Master's degree is a plus.

• Data Analysis: Proficiency in Python, R, or SQL for data manipulation and analysis.

• Visualization: Strong experience in data visualization tools such as Tableau, Power BI, or Looker to present data insights effectively.

• Statistical Analysis: Hands-on experience with statistical modeling tools (e.g., SPSS, SAS) and machine learning libraries (e.g., scikit-learn, TensorFlow) to build predictive models.

• Database Management: Experience with relational databases and data warehousing platforms such as SQL Server, Snowflake, or Google BigQuery.

• ERP/SCM Systems: Familiarity with enterprise resource planning (ERP) and supply chain management (SCM) tools like SAP, Oracle SCM.

• Strong problem-solving abilities and the ability to turn data into actionable insights.

• Excellent communication skills for translating technical data into clear business decisions.

• Attention to detail, with the ability to work both independently and collaboratively.

• High proficiency in Microsoft Excel, with advanced skills in pivot tables, VLOOKUP, and data analysis toolkits.

• 2-5 years of experience in data analysis, preferably in a supply chain or manufacturing environment.

• Experience with supply chain analytics tools like Llamasoft, Kinaxis RapidResponse, or Blue Yonder is highly desirable.

• Experience in predictive analytics and machine learning is a plus.

• APICS Certified Supply Chain Professional (CSCP) or Certified in Production and Inventory Management (CPIM).

• Certifications in Data Science or Machine Learning (e.g., Google Data Analytics, Microsoft Certified Data Analyst).

• Strong analytical and quantitative skills with a proven ability to solve complex problems.

• Ability to manage and analyze large datasets from various sources.

• Experience in process automation and optimizing workflows through technology.

• A passion for continuous learning and staying updated with the latest industry trends.