Supply Chain Data Analyst AP

In detail, you will:

Data Collection & Analysis:

• 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.

Supply Chain Optimization:

• 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.

Reporting & Visualization:

• 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.

Collaboration:

• 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.

Continuous Improvement:

• 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:

• A Bachelor’s Degree in Supply Chain Management, Data Science, Operations Research, Mathematics, Statistics, or Computer Science.
• 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 rational databases and data warehousing platforms such as SQL Server, Snowflake, or Google BigQuery.
• ERP/SCM Systems: Familiarity with enterprise resourcing planning (ERP) and supply chain management (SCM) tools like SAP, Oracle SCM.
• Strong problem-solving abilities and the ability to turn data into actional insights.
• Excellent communication skills for translating technical data into clear business decisions.
• Attention to detail, with ability to work both independently and collaboratively.
• High proficiency in Microsoft Excel with advanced skills in pivot tables, VLOOKUP, and data analysis toolkits.
• Experience:
• 3-5 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.
• Certifications (Preferred but not required):
• 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.