Job Description

About Advance Auto Parts:

Advance Auto Parts, Inc. is a leading automotive aftermarket parts provider that serves both professional installer and do-it-yourself customers. As of July 18, 2026, Advance operated 4,311 stores primarily within the United States, with additional locations in Canada, Puerto Rico and the U.S. Virgin Islands. The Company also served 786 independently owned Carquest branded stores across these locations and various Caribbean islands.

Advance Auto Parts India (AIIC) in Hyderabad, India, was established in 2019 to unlock operational efficiencies, increase levels of collaboration and support all regions in the US across IT, Financial, HR, Merchandizing, and Digital. With a large talent pool of over 450 employees, Advance works towards delivering the company’s mission: Passion for Customer ...Passion for Yes!

About Pricing Team:

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 Naïve 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

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