Job Summary
Join our dynamic team as a Lead Data Scientist, spearheading innovative data science solutions for Customer domain. In this role, you will be a key player in shaping the future of retail by leveraging cutting-edge technologies to enhance customer experiences.
The primary purpose of this role is to lead the development of cutting-edge data science, machine learning, and deep learning solutions to solve Lowe's retail problems at massive scale. This position will provide a wide range of strategic and technical leadership, research, and production ready implementations and solutions collaborating closely with engineering, product management and business partner teams. You will support diverse areas of the home improvement retail business including, but not limited to: predictive modeling; personalization and recommendation, visual search, assortment optimization, pricing and promotion in digital/eCommerce space; advanced computer vision algorithms, Generative AI (LLM, Diffusion) to improve store operations, safety, product data quality, customer shopping experience, associate productivity across 1700+ Lowe's physical stores, forecasting algorithms to optimize inventory and supply chain management across stores and distribution centers.
Initially this role will be focussed on building products in the Customer domain with a focus on Customer ID resolution and stitching. Although not required, experience with ML models and algorithms in Customer domain would be considered a positive.
Key Responsibilities
- Leads the full lifecycle of data science projects from inception to completion with full adherence to enterprise product and project management practices.
- Applies advanced data science, machine learning, and deep learning algorithms necessary to derive insights and to develop solutions on enterprise scale providing a competitive advantage to Lowe's business.
- Prepares final recommendations through effective storytelling and actionable insights for the relevant stakeholders, ensuring solutions are best-in-class, implementable and scalable in the business.
- Supports the development of automated self-service products and solutions for Lowe's business partners to effectively interpret data and build data products.
- Establishes and maintains robust data and AI governance practices and ensure data integrity, security, and compliance with relevant regulations.
- Highly proficient in Python or equivalent languages to build production ready data science capabilities.
- Maintains expert-level knowledge on industry trends, emerging technologies, leading research initiatives to explore their potential application in home improvement domain.
- Leads, mentors, and inspires a team of data scientists, fostering a culture of continuous learning, collaboration, and innovation.
- Provides guidance to more junior level scientists to translate requirements into an analytical approach; asks the right questions to understand the problem; validates understanding with Stakeholders and plans resources accordingly.
- Collaborates and communicates with cross functional stakeholders to provide updates and manage scope
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
• 6 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
• 3 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 2 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.
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What We Do
It’s curious to think of innovation and stability co-existing. But we pair a 100-year track record of success with a hunger to do things differently. Everyone is in the work — tackling complex problems where your impact can build back or build up the communities we serve.
We fill our halls with curious minds from all walks of life. Our differences make us stronger, which is why our leaders build cultures of recognition and inclusion. You are heard, and your curiosities are celebrated and championed here.
Why Work With Us
We have built a space where the curious can move freely. Up in title, up in skills, to the side with teams, or back to try something completely new. We help you find your path — because when you win, we all win.
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