Okay, I've searched for Supply Chain Data Analyst contract roles in the United States requiring 3+ years of experience, with proficiency in SQL and Python, focusing on supply chain forecasting and inventory planning skills. I have found 134 positions for you.

Sure. Here's the analysis:

Job Analysis:

The Supply Chain Data Analyst role is fundamentally about transforming complex, diverse data sets into actionable insights that drive supply chain efficiency and optimization. The candidate is expected to build and maintain robust ETL pipelines using SQL and Python, ensuring timely, accurate flow of supply chain data from various sources. The role demands a deep understanding of supply chain processes—forecasting, inventory planning, and optimization—so that data analysis is contextually relevant and directly impacts operational decision-making. Success in this role requires not just technical prowess in data manipulation libraries like pandas and NumPy, but also the ability to collaborate effectively with cross-functional teams such as logistics, operations, and engineering, to understand nuanced business challenges and co-create tailored, data-driven solutions. Automation and visualization play crucial roles here; the analyst must identify patterns and anomalies quickly and communicate them through clear dashboards and reports, driving continuous improvement and enabling rapid, evidence-based responses to dynamic supply chain conditions. The position also calls for agility, working under aggressive timelines, which implies that candidates must handle ambiguity, prioritize effectively, and integrate feedback rapidly to create impactful solutions.

Company Analysis:

PRI Global operates at the cutting edge of IT consulting, focusing heavily on innovation-driven, data-centric solutions, and digital transformation across enterprises. Positioned as a leading IT consulting firm in St. Louis and recognized for growth and diversification, PRI Global’s culture likely prizes adaptability, excellence, and bold, forward-thinking problem solving. Their emphasis on AI/ML, automation, and enterprise analytics suggests a fast-paced, technology-empowered environment that encourages continuous learning and cross-disciplinary collaboration. For the Supply Chain Data Analyst role, this means working within a company that values innovation and developing scalable, future-proof solutions that align with evolving business needs. The role sits at the intersection of IT and core business operations, meaning the analyst may have significant visibility and influence across functions and possibly with senior leadership, requiring strong communication and strategic alignment skills. The company’s growth trajectory also implies that this role could be critical in scaling operations and enhancing competitive advantage through data mastery. Understanding PRI’s mission to enable business transformation through technology will be vital for a candidate to integrate culturally and strategically, showing enthusiasm for both technical challenges and business impact.

Absolutely. Here are some mock interview questions that could come up:

• Behavioral: Tell me about a time when you had to develop a data pipeline under tight deadlines. How did you prioritize your tasks, and what was the outcome?
• Behavioral: Describe an experience where you identified an anomaly in supply chain data that led to a significant process improvement. How did you communicate your findings?
• Behavioral: Give an example of how you have collaborated with cross-functional teams to deliver a data-driven solution. What challenges did you face, and how did you overcome them?
• Behavioral: Share a situation where you had to learn a new tool or technology quickly to complete a project. How did you approach it?
• Technical: Can you walk me through your process for building an ETL pipeline using SQL and Python? What best practices do you follow to ensure data quality and efficiency?
• Technical: How do you use Python libraries such as pandas and NumPy to manipulate supply chain data? Can you provide a specific example?
• Technical: What forecasting models or methodologies have you applied in inventory planning, and how do you validate their accuracy?
• Technical: Have you created dashboards or visualization tools for non-technical stakeholders? What tools do you prefer and why?
• Situational: Imagine that your automated data pipeline suddenly fails, and you have a tight deadline to report key supply chain KPIs. How would you handle this situation?
• Situational: Suppose cross-functional teams have conflicting priorities that impact your data project’s requirements. How would you navigate these differences to deliver a successful outcome?
• Situational: If you discover a discrepancy in the data that could indicate a larger operational issue but the stakeholders are skeptical, how would you proceed?
• Company Fit: What excites you most about working with PRI Global, particularly in a contract role focused on supply chain analytics?
• Company Fit: How do you see your experience and values aligning with a company that emphasizes innovation, growth, and digital transformation?
• Company Fit: PRI Global focuses on cutting-edge IT solutions. How do you stay current with emerging technologies and trends in data analytics and supply chain management?
• Candidate Questions: Can you share how the supply chain data analytics team collaborates with other departments within PRI Global?
• Candidate Questions: What are the immediate challenges or projects the new Supply Chain Data Analyst will be expected to address in the first six months?
• Candidate Questions: How does PRI Global support continuous learning and professional development, especially for contract employees working with evolving technologies?