Data Scientist_ML Ops, Pricing

About Lowe's

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

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

Job Summary:

The primary purpose of this role is to provide advanced analytical capabilities to support data science initiatives. This position gains experience in various areas including, but not limited to: predictive modelling; Time Series and Demand Forecasting, Optimization, Linear and non linear curve fitting, Price Elasticity, feature engineering, model development and management, production deployment of the models, scalability of systems and measurement in the realm of price optimization, dynamic pricing and promotion analytics. A MLE solves complex problems that require deploying models at scale.

Roles and Responsibilities:

• Provide advanced analytical capabilities to support data science and machine learning initiatives across key business domains.
• Design, develop, and deploy predictive models for applications such as time series forecasting, demand prediction, optimization, price elasticity, and promotion analytics.
• Perform feature engineering, model development, validation, and performance monitoring to ensure accuracy and business relevance.
• Implement scalable machine learning solutions using Python, PySpark, and distributed computing environments.
• Deploy models at scale using GCP (AI Vertex), Kubernetes, Docker containers, and APIs (FastAPI/Flask).
• Orchestrate and automate ML pipelines using Airflow and MLOps frameworks.
• Manage model lifecycle through MLFlow or similar tools to ensure robust model governance and reproducibility.
• Collaborate with cross-functional teams to integrate models into production systems and measure their impact.
• Optimize model performance, scalability, and efficiency for real-time or batch inference.
• Stay current with emerging trends in AI/ML, cloud technologies, and pricing optimization methodologies.

Required Minimum Qualifications:

• 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 a related field) AND 4-8 years of experience in Predictive Analytics, Machine learning and Statistical modelling with Python, SQL AND GCP or any other cloud data technologies
  
  OR
• Master's Degree in Mathematics, Statistics, Physics, Economics, Engineering, Computer Science, Data or Information Science, or related quantitative analytic field AND 3-7 years of experience in Predictive Analytics, Machine learning and Statistical modelling with Python, SQL AND GCP or any other cloud data technologies.
  
  OR
• Ph.D. in Mathematics, Statistics, Physics, Economics, Engineering, Computer Science, Data or Information Science, or related quantitative analytic field AND 2-5 year of experience in Predictive Analytics, Machine learning and Statistical modelling with Python, SQL AND GCP or any other cloud data technologies.

Primary Skills (must have):

• 2 years of experience executing and deploying data science, machine learning, deep learning, and generative AI solutions, preferably in a large-scale enterprise setting
• 1 year of SQL and programming experience
• Bachelor's degree in mathematics, statistics, physics, economics, engineering, computer science, data, information science, or related quantitative analytic field (or equivalent work experience in lieu of degree)

Secondary Skills:

• 1 year of experience using multiple data systems and sources
• 1 year of experience working with cross-functional partners
• Master's degree in mathematics, statistics, physics, economics, engineering, computer science, data, information science, or related quantitative analytic field

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.