About Lowe’s

Lowe’s Companies, Inc. (NYSE: LOW) is a FORTUNE® 50 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.

About The Team

Product Discovery team is responsible for managing the Search & Recommendation functions to help customers find the relevant products. Team is focused on building scalable nextgen models using AI /ML to enhance product discovery by personalizing and optimizing the customer experience. Their key goals are:

• Personalized Recommendations: Build recommendation systems that suggest products based on user behavior and preferences.
• Smarter Search: Use AI techniques like NLP to improve search accuracy and relevance.
• Dynamic Personalization: Tailor product listings and content to individual users, boosting engagement and conversion.
• User Insights: Leverage data to refine discovery algorithms and enhance the customer journey.
• Scalable Infrastructure: Ensure algorithms remain efficient as data and user interactions grow.
• Continuous Improvement: Continuously refine models through feedback loops and performance metrics.
  
  

Ultimately, the team aims to drive higher conversions, better user experience, and operational efficiency by delivering smarter, scalable product discovery through a data driven approach.

Job Summary

We are seeking a talented Principal Data Scientist to lead the development of Product Search and Recommendation systems. The ideal candidate will have a strong background in natural language processing (NLP), machine learning, deep learning, and semantic understanding, and will be passionate about transforming the way users discover relevant content. As a Principal Data Scientist, you will be responsible for driving the vision and strategy for Ecommerce search and personalized recommendation systems, leveraging state-of-the-art techniques such as transformer models, embeddings, and knowledge graphs. You will collaborate closely with product teams, engineers, and business stakeholders to enhance user experience and business outcomes.

Roles & Responsibilities

Leadership & Strategy

Lead the development of cutting-edge Search and recommendation algorithms that improve relevance, personalization, and user engagement.

Define and execute the strategy for semantic understanding and recommendations, aligning with overall business goals.

Work cross-functionally with product managers, engineers, and data scientists to drive the roadmap for search and recommendation improvements.

• Search & NLP Expertise Lead the design and implementation of Search/Recommendation models that go beyond traditional keyword matching to understand user intent and context. Apply advanced NLP techniques such as transformers (BERT, GPT, T5), word embeddings, and contextualized word representations to enhance search relevance. Use techniques like sentence embeddings, document embeddings, and similarity measures to build scalable search systems that understand semantic meaning.
• Model Development & Experimentation Conduct research and experiments to design, develop, and validate new Search models and Recommendation techniques. Continuously test, measure, and optimize models through A/B testing, real-time metrics, and user feedback loops. Develop approaches to handle large-scale data, ensuring the models can be deployed efficiently in production environments.
• Collaboration & Mentorship Lead and mentor a team of data scientists, guiding them in the development of semantic models and complex recommendation algorithms. Foster a culture of knowledge sharing and collaboration across teams to ensure that the best practices are followed in model development and deployment. Collaborate with engineers & product managers to ensure the effective integration of models into scalable production systems.
• Thought Leadership Stay up to date with the latest research in Search, NLP, and recommendation systems. Evangelize the use of cutting-edge techniques within the company to drive innovation in search and recommendations.
  
  

Years Of Experience

• 8 years of experience executing and deploying data science, machine learning, deep learning, and generative AI solutions, preferably in a large-scale enterprise setting (fewer years may be accepted with a master’s or doctorate degree)
• 8 years of programming experience (fewer years may be accepted with a master's or doctorate degree)
• 5 years of SQL experience and knowledge of various statistical modeling or machine learning techniques
• Bachelor's degree in mathematics, statistics, physics, economics, engineering, computer science, data or information science, or related quantitative analytic field (or equivalent work experience in lieu of degree)
  
  

Candidates with Doctorate or Master’s degree are preferred

Education Qualification & Certifications

• Bachelor’s degree (Required): Mathematics, Statistics, Physics, Economics, Engineering, Computer Science, Data or Information Science, or related quantitative analytic field (or equivalent work experience in a related field)
• Doctorate Degree (Preferred): Mathematics, Statistics, Physics, Economics, Engineering, Computer Science, Data or Information Science, or related quantitative analytic field
  
  

Skill Set Required

Machine Learning & AI

• Supervised/unsupervised learning (e.g., regression, clustering)
• Deep learning (CNNs, RNNs, Transformers)
• Natural Language Processing (NLP) for search relevance
• Experience with generating vector embeddings
  
  

Statistical & Mathematical Expertise

• Probability, statistics, and A/B testing
  
  

Leadership & Collaboration

• Cross-functional team collaboration (engineering, product, design)
• Mentoring junior data scientists
• Communicating technical concepts to non-technical stakeholders
  
  

Tools & Frameworks

• Programming (Python, R, Scala)
• ML frameworks (TensorFlow, PyTorch, scikit-learn)
• Version control (Git)
  
  

Performance Evaluation

• Model evaluation using metrics (precision, recall, NDCG)
• Online learning and incremental model updates
  
  

Understanding of Data Engineering & Infrastructure

• Big data technologies (Apache Spark, Hadoop)
• Data pipeline management (ETL processes)
• Database management (SQL, NoSQL, Elasticsearch)
• Cloud platforms (AWS/GCP/Azure)
  
  

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.

Starting rate of pay may vary based on factors including, but not limited to, position offered, location, education, training, and/or experience. For information regarding our benefit programs and eligibility, please visit https://talent.lowes.com/us/en/benefits.