Lead Analyst, Pricing Analytics

You will play a crucial role in developing and maintaining descriptive and predictive analytics models and tools that support Lowe's pricing strategy. Working closely with the Pricing team, you will translate pricing goals and objectives into data and analytics requirements. By leveraging a combination of open source and commercial data science tools, you will gather and wrangle data to provide data-driven insights, trends, and identify anomalies. Utilizing suitable statistical and machine learning techniques, you will address relevant questions and offer retail recommendations. Collaboration with product and business teams is essential to drive continuous improvement, incorporating feedback throughout development to maintain a best-in-class position in the pricing space. Your responsibilities will include translating pricing strategy and business objectives into analytics requirements, implementing processes for data collection and preparation, conducting data validation and outlier detection, designing and implementing statistical and machine learning models, ensuring model accuracy, and applying machine learning outcomes to business use cases. Educating the pricing team on interpreting and utilizing machine learning model results, designing and executing experiments to evaluate price changes, performing advanced statistical analyses, and managing analytics projects are key aspects of this role. You will also lead the exploration of new analytical techniques, collaborate with various teams, stay updated on industry developments, and mentor junior analysts to foster skill development and team growth. With 6-12 years of relevant experience, you should hold a Bachelor's or Master's degree in Engineering, Business Analytics, Data Science, Statistics, Economics, or Mathematics. Your skill set should include expertise in advanced quantitative analysis, statistical modeling, and machine learning models, along with experience in regression, hypothesis testing, time series analysis, predictive modeling, and other analytical concepts. Proficiency in SQL, Python, R, SAS, enterprise-level databases, data visualization tools, and cloud platforms is required. Technical expertise in Alteryx and Knime is desired for this role.,