Innovate in Bengaluru

This position is based at our on-site office in Bengaluru. Lowe's offers an ultramodern work environment, complete with cutting-edge technology, collaborative workspaces, an on-site gym and clinic, and other perks to enhance your work experience. 

Lowe’s is a FORTUNE® 100 home improvement company serving approximately 16 million customer transactions a week in the United States. With total fiscal year 2024 sales of more than $83 billion, Lowe’s operates over 1,700 home improvement stores and employs approximately 300,000 associates. Based in Mooresville, N.C., Lowe’s supports the communities it serves through programs focused on creating safe, affordable housing, improving community spaces, helping to develop the next generation of skilled trade experts and providing disaster relief to communities in need. For more information, visit Lowes.com.

Lowe’s India, the Global Capability Center of Lowe’s Companies Inc., is a hub for driving our technology, business, analytics, and shared services strategy. Based in Bengaluru with over 4,500 associates, it powers innovations across omnichannel retail, AI/ML, enterprise architecture, supply chain, and customer experience. From supporting and launching homegrown solutions to fostering innovation through its Catalyze platform, Lowe’s India plays a pivotal role in transforming home improvement retail while upholding strong commitment to social impact and sustainability. For more information, visit Lowes India

Experience: 3–6 Years | Location: In-Office

Role Overview

Develop and maintain descriptive and predictive analytics models to support Lowe’s pricing strategy. Collaborate with Pricing and cross-functional teams to translate business objectives into data-driven solutions using advanced statistical and machine learning techniques.

Responsibilities & Skills

• Translate pricing goals into analytics requirements and design data pipelines for large datasets.
• Build and validate statistical and machine learning models for pricing optimization and anomaly detection.
• Conduct A/B tests, multivariate experiments, and advanced statistical analyses (regression, causal inference, Bayesian methods).
• Automate processes and create dashboards using tools like Power BI/Tableau for actionable insights.
• Collaborate with Pricing, Merchandising, and IT teams to deliver innovative solutions and continuous improvement.
• Proficiency in SQL, Python/R, SAS; experience with Hadoop/Teradata, cloud platforms (AWS/GCP/Azure), and visualization tools.

Experience :

• 3+ years in advanced analytics, machine learning, and pricing/revenue management.
• Proficiency in SQL, Python/R, SAS; experience with Hadoop/Teradata, cloud platforms (AWS/GCP/Azure), and visualization tools.

Experience: 4–5 Years | Location: In-Office

Role Overview

Drive data-driven insights for Merchandising Finance by analyzing large datasets, forecasting trends, and influencing category strategies. Collaborate with cross-functional teams to optimize product performance, pricing, and customer engagement.

Responsibilities & Qualifications

• Extract, curate, and analyze large datasets to assess product/category performance and identify growth opportunities.
• Build predictive and scenario models for demand forecasting and category optimization.
• Develop dashboards and visualizations (Power BI/Tableau) to communicate insights effectively.
• Partner with Merchandising, Marketing, and Finance teams to align strategies and influence decisions.
• Present actionable insights to senior leadership and recommend data-driven solutions.
• Ensure data integrity and mentor junior analysts.
• Required: Bachelor’s in Business, Economics, Data Science, or related field; 4–5 years analytics experience in merchandising/marketing; proficiency in SQL, Excel, Python, Power BI; strong data modeling and problem-solving skills.
• Preferred: Master’s degree, retail loyalty program experience, home improvement retail background.

Lowe's is an equal opportunity employer and administers all personnel practices without regard to race, color, religious creed, sex, gender, age, ancestry, national origin, mental or physical disability or medical condition, sexual orientation, gender identity or expression, marital status, military or veteran status, genetic information, or any other category protected under federal, state, or local law.