Okay, I've searched for Supply Chain Data Scientist positions in Chicago that require a Bachelor's degree, involve machine learning and advanced analytics, and require over a year of experience with SQL and Python. I found 25 positions for you to review.

Sure. Here's the analysis:

Job Analysis:

The Supply Chain Data Scientist role at Conagra is designed to harness data science, AI, and advanced analytics to drive decision-making across the supply chain. The primary objective is to create and implement data-driven solutions that improve operational efficiency and optimize processes. Key responsibilities include developing advanced analytics and machine learning models, conducting root-cause analyses, and collaborating with cross-functional teams to integrate insights into existing Business Intelligence systems. Candidates must possess strong programming skills in SQL and Python, indicating a deep proficiency in data manipulation and analysis. Additionally, familiarity with tools like Databricks and Power BI is crucial, as the role requires monitoring and optimizing data products while enhancing user experience. A successful candidate will navigate complex datasets to draw actionable insights and demonstrate strong problem-solving abilities. Performance expectations likely include measurable improvements in supply chain efficiencies and contributions to a culture that prioritizes data-led decision-making, especially within the first 6-12 months of employment, where demonstrating the ability to generate valuable analytics and foster collaborative problem-solving will be critical.

Company Analysis:

Conagra Brands is positioned as a leader in the food industry with a strong heritage and an innovative spirit reminiscent of a startup. This unique combination shapes the work environment into one that values agility, collaboration, and an openness to challenge conventional practices. The company emphasizes a diverse and inclusive culture, fostering creativity and collective problem-solving, which aligns well with the open-ended and collaborative nature of the Supply Chain Data Scientist role. Team dynamics are such that the person in this role will work closely with various teams to develop data solutions, suggesting an expectation for visibility and influence on strategic decisions across the organization. Given Conagra’s commitment to continuous improvement and its focus on building stronger brands and products, this role serves as a critical element in advancing the company’s operational capabilities and innovation targets. Candidates who align with the company’s values of integrity, external focus, and results-oriented performance will likely thrive, contributing significantly to the overarching goal of enhancing Conagra's analytics maturity and maintaining its competitive edge in the food market.

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

• Tell me about a time when you had to solve a complex data problem. What approach did you take and what was the outcome?
• Describe a project where you utilized machine learning algorithms. What challenges did you face and how did you overcome them?
• Can you provide an example of how you collaborated with team members to achieve a data-driven objective?
• In your past experience, how have you utilized SQL and Python in your projects? Can you discuss a specific instance?
• Explain your experience with advanced analytics or data mining. How would you use these skills in our supply chain context?
• How would you approach developing a predictive model for optimizing supply chain logistics?
• Imagine you are faced with incomplete data while trying to improve an existing analytics product. How would you tackle this challenge?
• Given a situation where you identify a significant inefficiency in the supply chain, what steps would you take to analyze and address it?
• Why are you interested in working at Conagra Brands specifically, and what do you find appealing about our values and culture?
• How do your career goals align with the direction that Conagra is heading in the food industry?
• What questions do you have regarding the team structure and collaborative opportunities within our data science group?
• Can you share your thoughts on the importance of a diverse and inclusive workplace and how it contributes to effective business solutions?
• What do you see as the biggest challenge for the supply chain industry in terms of data analytics over the next five years?