Sr. Lead Analyst, Supply Risk

As a Sr. Lead Analyst in Supply Risk at Chick-fil-A, you'll be responsible for developing and implementing sophisticated data models that inform supply chain strategies. Your day-to-day tasks include creating interactive visualizations, analyzing supplier-related data, and collaborating with cross-functional teams. Another crucial responsibility is predictive modeling for continuity planning, which helps ensure that our supply chain remains reliable and efficient.

To excel as a Sr. Lead Analyst at Chick-fil-A, you should have a Bachelor's Degree in Data Science, Analytics, Supply Chain Management, or a related field. You also need at least 4 years of experience in fields like Supply Chain, Risk Management, or Data Analytics. Proficiency in data analytics tools such as Python and SQL, along with experience in visualization tools like Tableau or Power BI, is also essential.

In the role of Sr. Lead Analyst, Supply Risk at Chick-fil-A, having strong technical skills is critical. You should be proficient in data analytics and statistical modeling tools like Python, R, and SQL. Familiarity with data visualization platforms such as Tableau and Power BI is also important, as you'll need to create visual reports and dashboards that communicate insights to stakeholders effectively.

The Sr. Lead Analyst, Supply Risk at Chick-fil-A plays a collaborative role by working closely with various cross-functional teams. You'll integrate data analytics into decision-making and partner with IT to ensure data integrity. Additionally, you will provide training and support on data interpretation to enhance the overall analytics capabilities within the organization.

As a Sr. Lead Analyst at Chick-fil-A, you can expect a flexible working environment that accommodates both in-person collaboration and virtual work. This model not only fosters community but allows you to engage in meaningful interactions with colleagues. The company's culture emphasizes innovation, teamwork, and continuous improvement, making it an exciting place to grow your career.

In your answer, highlight specific projects or models you've developed that inform supply risk decisions. Discuss the tools you used—like Python or R—and how they helped you translate data into actionable insights. Focus on the importance of understanding the data's implications.

Describe your process for developing predictive models, including data selection, model testing, and validation. Emphasize your experience with analyzing trends, as well as any statistical techniques or machine learning methods you've applied to ensure reliability in your models.

Mention your proficiency with tools like Tableau or Power BI, explaining how you create dashboards and visual reports to convey complex data clearly. Discuss specific instances where your visualizations helped drive decision-making in a team setting.

Share a specific example where your analytical skills helped solve a significant issue in supply risk or chain management. Explain your thought process, the data you analyzed, and the final outcome, which demonstrates your problem-solving abilities.

Discuss the importance of data quality management practices you adhere to. Your response should include any protocols you follow for data validation, as well as how you work with IT teams to maintain high standards of data integrity throughout projects.

Provide insight into your routine for continuous learning, such as attending workshops, webinars, or following industry publications and thought leaders. Emphasize your proactive stance on incorporating new technologies or techniques into your analyses.

Share an example that showcases your ability to convey complex analytical concepts in a simplified manner. Highlight how you tailored your communication, and the tools or techniques you used to engage your audience effectively.

Discuss your past experiences working directly with suppliers, focusing on any initiatives you've led to improve data-sharing practices. Highlight the outcomes of these collaborations in terms of risk mitigation or operational efficiency.

Provide your perspective on current challenges such as geopolitical disruptions, raw material shortages, or sustainability concerns. Discuss how data analytics can help address these challenges and improve overall supply chain resilience.

Elaborate on strategies you use to prioritize competing tasks effectively. Mention any tools or methodologies, such as time management techniques or project management software, that help you stay organized while ensuring deadlines are met.