Principal Data Scientist – Product Search & Recommendations

Job Type: Full-time

Location: Bengaluru, Karnataka

About Lowe’s

Lowe’s is a FORTUNE® 100 home improvement leader, serving nearly 16 million customer transactions per week across the United States. With FY 2024 sales exceeding $83 billion, Lowe’s operates 1,700+ stores and employs about 300,000 associates. Headquartered in Mooresville, N.C., Lowe’s supports communities through initiatives focused on safe housing, community spaces, skilled trades development, and disaster relief.

About Lowe’s India

Lowe’s India is the Global Capability Center of Lowe’s Companies Inc., driving the organization’s technology, analytics, business operations, and shared services. Located in Bengaluru, the center has 4,500+ associates powering innovations across omnichannel retail, AI/ML, enterprise systems, supply chain, and customer experience. It also fosters innovation through its Catalyze platform and invests heavily in social impact and sustainability initiatives.

About the Product Discovery Team

The Product Discovery team builds next-generation AI/ML systems to help customers find relevant products through Search and Personalization. Key focus areas include:

1. Personalized Recommendations using user behavior and preference data

2. AI-driven Search leveraging NLP for relevance and accuracy

3. Dynamic Personalization of product listings and content

4. Data-driven Insights for continuous customer experience improvement

5. Scalable Systems to support increasing data and user traffic

6. Model Improvement Loops through metrics and feedback

The team’s mission is to increase conversions, enhance user experience, and optimize discovery through advanced, scalable AI solutions.

Job Summary

Lowe’s is seeking a Principal Data Scientist to lead the development of advanced Search and Recommendation systems for e-commerce. The ideal candidate has strong expertise in NLP, deep learning, semantic understanding, transformers, embeddings, and large-scale ML systems.

You will define the vision for Lowe’s search and recommendation strategy, lead complex model development, and work closely with engineering, product, and business teams to drive significant user and business impact.

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Roles & Responsibilities

Leadership & Strategy

• Lead development of cutting-edge search and recommendation algorithms

• Define strategy for semantic understanding and personalization

• Partner cross-functionally with product managers, engineers, and data scientists

Search, NLP & Relevance

• Build models that understand user intent beyond keyword matching

• Apply transformer-based architectures (BERT, GPT, T5)

• Utilize embeddings (sentence, document, vector similarity) for semantic search

Modeling & Experimentation

• Research, design, and validate new search and recommendation models

• Run A/B tests and monitor real-time performance metrics

• Build scalable models for large datasets and production deployment

Collaboration & Mentorship

• Lead and mentor a team of data scientists

• Drive knowledge sharing and best practices

• Ensure smooth integration of models into production systems

Thought Leadership

• Stay updated with advancements in NLP, LLMs, search ranking, and recommendation systems

• Champion the adoption of cutting-edge approaches across teams

Required Experience

• 8+ years in data science / ML / DL / GenAI (less with Master’s/PhD)

• 8+ years programming experience (less with advanced degrees)

• 5+ years SQL experience

• Experience deploying models at enterprise scale

• Bachelor’s degree in a quantitative field (Math, Stats, CS, Engineering, Physics, etc.)

• Master’s or PhD preferred

Required Skills

Machine Learning & AI

• Supervised & unsupervised learning

• Deep learning (CNN, RNN, Transformers)

• NLP for search relevance

• Embedding generation & similarity systems

Statistics & Experimentation

• A/B testing

• Probability & statistical modeling

Collaboration & Leadership

• Cross-functional communication

• Mentoring junior data scientists

• Translating complex ML concepts for non-technical stakeholders

Tools & Technologies

• Python, R, Scala

• TensorFlow, PyTorch, scikit-learn

• Git

• Big data tools (Spark, Hadoop)

• ETL pipelines & data management

• SQL & NoSQL databases; Elasticsearch

• Cloud: AWS/GCP/Azure

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