Lead Analyst, Pricing Analytics

About Lowe's

Lowe&aposs Companies, Inc. (NYSE : LOW) is a FORTUNE® 50 home improvement company serving approximately 17 million customer transactions a week in the U.S. With total fiscal year 2022 sales of over $97 billion, approximately $92 billion of sales were generated in the U.S., where Lowe&aposs operates over 1,700 home improvement stores and employs approximately 300,000 associates. Based in Mooresville, N.C., Lowe&aposs supports the communities it serves through programs focused on creating safe, affordable housing and helping to develop the next generation of skilled trade experts.

About Lowe's India

At Lowe&aposs India, we are the enablers who help create an engaging customer experience for our $97 billion home improvement business at Lowe&aposs. Our 4000+ associates work across technology, analytics, business operations, finance & accounting, product management, and shared services. We leverage new technologies and find innovative methods to ensure that Lowe&aposs has a competitive edge in the market.

About the Team

The Pricing Analytics team assists pricing managers and merchants in defining and optimizing pricing strategies for different product categories across various channels. The team uses advanced analytics to forecast and measure the impact of pricing decisions, develop strategic price zones, recommend price adjustments, and identify sales and margin opportunities to help achieve company targets.

Job Summary

The primary purpose of this role is to develop and maintain descriptive and predictive analytics models and tools that support Lowe&aposs pricing strategy. Collaborating closely with the Pricing team, the analyst will help translate pricing goals and objectives into data and analytics requirements. Utilizing both open source and commercial data science tools, the analyst will gather and wrangle data to deliver data driven insights, trends, and identify anomalies. The analyst will apply the most suitable statistical and machine learning techniques to answer relevant questions and provide retail recommendations. The analyst will actively collaborate with product and business team, incorporating feedback through out the development to drive continuous improvement and ensure a best-in-class position in the pricing space.

Roles & Responsibilities

Core Responsibilities :

• Translate pricing strategy and business objectives into analytics requirements.
• Develop and implement processes for collecting, exploring, structuring, enhancing, and cleaning large datasets from both internal and external sources.
• Conduct data validation, detect outliers, and perform root cause analysis to prepare data for statistical and machine learning models.
• Research, design, and implement relevant statistical and machine learning models to solve specific business problems.
• Ensure the accuracy of model results and build trust in their reliability.
• Apply machine learning model outcomes to relevant business use cases
• Educate the pricing team on how to effectively interpret and utilize machine learning model results.
• Assist in designing and executing A / B tests, multivariate experiments, and randomized controlled trials (RCTs) to evaluate the effects of price changes.
• Perform advanced statistical analyses (e.g., causal inference, Bayesian analysis, regression modeling) to extract actionable insights from experimentation data.
• Lead and manage analytics projects, ensuring they are completed on time, within scope, and aligned with business objectives.
• Lead the exploration and implementation of new analytical techniques, tools, and industry best practices.
• Collaborate with teams such as Pricing Strategy & Execution, Analytics COE, Merchandising, IT, and others to define, prioritize, and develop innovative solutions.
• Promote future-proof practices and holistic solutions, adopt new tools and techniques, and identify opportunities for enhancing analytical solutions.
• Keep up to date with the latest developments in data science, machine learning, statistics, and experimentation techniques.
• Lead and mentor junior analysts, fostering skill development and growth within the team.

Years of Experience :

Education Qualification & Certifications (optional)

Required Minimum Qualifications :

Skill Set Required :

Primary Skills (must have)

Secondary Skills (desired) :

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Skills Required

Hadoop, Alteryx, Power Bi, Sas, Tableau, Knime, Teradata, Sql, Statistical Modeling, Gcp, Db2, Machine Learning, Azure, Oracle, Python, Aws