Expand your career possibilities.

Thank you for dedicating your time and talent to Lowe’s. We want to give you more opportunities to learn and grow, so if you find a position you’re interested in below, we encourage you to apply!

Find Your Home to More Possibilities.

Job Summary Lowe's Forecasting team is seeking a motivated Sr Data Scientist – Forecasting (Machine Learning). You will build and deploy state of the art predictive models for use cases such as item-location demand forecast, labor & truck planning, inventory management, supply chain optimization, financial expense prediction. Join us if you are also excited about extending machine learning and data engineering to practical, scalable, time and memory efficient applications. Lowe's Home Improvement is a rapid - growing retailer (Fortune 50 companies) with millions of customers & products and billions of records. Here at Lowe's Forecasting, you will have the freedom and ownership to lead cutting-edge research and impactful projects, in a collaborative and flexible environment with work-life balance. Key Responsibilities:

• Lead the full development lifecycle from POC, MVP to Production of ML models.

• Develop and maintain pipelines for training and deploying ML models.

• Collaborate with data scientists, data engineers and product managers to ensure that business specifications are translated into flexible, scalable, and maintainable solutions.

• Research and stay abreast of state-of-the-art machine learning technologies.

• Follow code standards and best practices.

• Prepare and present data stories to business partners for adoption.

• Mentor junior team members.

Where You’ll Be

• Associates are required to relocate to the Charlotte region to foster collaboration and facilitate improved testing and support.

• Lowe’s supports a Flex Office concept where in-person work is required two days per week at the Charlotte Tech Hub

• Most business meetings are planned around the Eastern time zone.

Required 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 years of experience in analytics AND 2 years of programming experience (Python, Java, Scala, Rust, etc.)
OR
• Master's Degree in Mathematics, Statistics, Physics, Economics, Engineering, Computer Science, Data or Information Science, or related quantitative analytic field AND 2 years of experience in analytics AND 1 year of programming experience (Python, Java, Scala, Rust, etc.)
OR
• Ph.D. in Mathematics, Statistics, Physics, Economics, Engineering, Computer Science, Data or Information Science, or related quantitative analytic field AND 1 year of experience in analytics
Also
• Knowledge of SQL and various statistical modeling or machine learning techniques
Preferred Qualifications
• Ph.D. degree in Mathematics, Statistics, Physics, Economics, Engineering, Computer Science, Data or Information Science, or related quantitative analytic field
• 3 years of experience performing predictive analytics at a large scale enterprise
• 3 years of experience in data science or advanced analytics in industry
• SQL Experience
• Programming experience (Python, Java, Scala, Rust, etc.)
• Experience using multiple data systems and sources (such as Hadoop, Spark, Aster, Teradata, etc.)

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 2023 sales of more than $86 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 and helping to develop the next generation of skilled trade experts. For more information, visit Lowes.com.

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.