DATA SCIENTIST- STORE DEV

SUMMARY At AutoZone, we rely on insightful data to power our systems and solutions. We’re seeking an experienced data scientist to deliver that insight to us daily. Our ideal team member will have the mathematical and statistical expertise you’d expect, but a natural curiosity and creative mind that’s not so easy to find. As you mine, interpret, and clean our data, we will rely on you to ask questions, connect the dots, and uncover opportunities that lie hidden within—all with the ultimate goal of realizing the data’s full potential. KEY RESPONSIBILITIES · Research, test, and apply predictive modeling techniques to historical store performance and related trade area demographics and store characteristics to determine those factors that most reliably predict store performance. Create predictive models based on those factors that will provide Research and Real Estate sales estimates for the potential trade areas · Participate in the various stages of the new store approval process and perform ad-hoc analysis to answer questions from the Executives · Collaborate with different functional teams using advanced data modeling and analysis techniques to discover insights that will guide strategic decisions · Serve as the spatial analytics hub for the entire organization and answer any question with a “where” component · Create predictive models to estimate sales to strategize our International expansion · Assess the effectiveness and accuracy of new data sources and data gathering techniques · Develop custom data models and algorithms to apply to data sets · Develop processes and tools to monitor and analyze model performance and data accuracy · Collaborate with management to develop an understanding of needs · Research and devise innovative statistical models for data analysis · Communicate findings to all stakeholders · Enable smarter business processes and implement analytics for meaningful insights · Keep current with technical and industry developments REQUIREMENTS · Master’s degree in statistics, information systems, data science, analytics, engineering, finance, or another related field · 2 to 4 years of relevant experience in statistical analysis, advanced modeling techniques, data mining, and business analysis. These methods include techniques such as Linear Regression, Random Forest, Time Series Analysis, Gradient Boosted Models, TensorFlow, Clustering Analysis, etc. · Experience in Alteryx, R, Python, SAS, GIS tools, SQL, Excel, Tableau, and similar tools to extract, cleanse, manipulate and validate data from a variety of sources · Excellent communication skills; persuasive in presenting complex data and concepts to non-technical audiences