Associate Pricing Scientist

Job Summary

The Advance Auto Parts India Pricing team is part of global pricing and merchandizing organization. It is responsible for determining the best prices for automotive parts by combining business strategy, competitive intelligence, analytics, and data science to grow revenue, improve margins, and enhance customer experience across our North America business.

Role and Responsibilities

• Develop Analytics solutions predictive model for pricing and promotions e.g. price elasticity models, customer segmentation, discount optimization with minimum supervision
• Perform statistical analysis for hypothesis testing e.g. A/B testing to predict the impact of pricing changes on test skus/regions.
• Collaborate with the pricing strategy and insights team to conceptualize and develop the prototype of analytics solutions
• Involve in discussions with stakeholders and gather requirements showcasing the analysis, interpretations findings and scale the solutions to next level
• Forecasting of demand drivers using Structural Time Series and Naive Bayes approach and also by analyzing the impact of micro-economics factors on category/region performance
• Build intelligent systems to capture and model the vast amount of behavior data to enrich the content understanding with behavioral information for promotional strategies

Requirements

• 2 to 4 years of relevant experience as data scientist or pricing scientist in retail/ecom analytics
• Masters/PhD in management science, data science, economics, mathematics from reputed institutes is preferable
• Should have a strong fundamental understanding of price elasticity, price-demand curves, econometrics and optimizations techniques.
• Strong applied knowledge of machine learning covering the landscape of classification, regression and with in-depth interpretation of outcomes for pricing and promotions
• Advance level proficiency in python/R, PowerBI, Snowflake/SQL
• Ability to effectively communicate and explain the analytical model approach and output with the business stakeholders
• Applicants should have strong fundamental understanding and research experience in Data Wrangling, Statistical Analysis, Predictive Modeling using Machine Learning (Regression and Classification), Clusters Segmentation, Time Series Forecasting (ARIMA, SARIMAX) etc.
• Strong business acumen to understand the retail and merchandizing functions.
• Excellent communication and collaborative skills with the ability to work in cross functional multi-cultural global teams