Overview

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: machine learning/AI; predictive/prescriptive modeling; personalization and recommendation algorithms; natural language processing and text mining; search recall, precision, ranking, and related problems; large scale forecasting; optimization and mathematical programming with applications in labor scheduling, inventory and capacity planning, network flows, assortment optimization, and supply chain optimization.

RESPONSIBILITY STATEMENTS
Mines and extracts data and applies statistics and algorithms necessary to derive insights for Lowe’s and Lowe’s Digital
Supports the generation of an automated insights generation framework for Lowe’s business partners to effectively interpret data
Provides actionable insights through data science on Personalization, Search & Navigation, SEO & Promotions, Supply Chain, Services, other company priorities, etc.
Tracks success of Lowe’s through the development of dashboard reports that measure financial results, customer satisfaction, and engagement metrics
Conducts deep statistical analysis, including predictive and prescriptive modeling in order to provide a competitive advantage at Lowe’s
Maintains up-to-date knowledge on industry trends, emerging technologies, and new methodologies and applies it to projects as well as using it to guide team members
Serves as a leading member on automation and analytical projects, collaborating across functions in Lowe’s and Lowe’s Digital

Company:

Lowe’s Companies, Inc.

Qualifications:

Required Education / Experience
Bachelor’s Degree in Computer Science, Statistics, Physics, Econometrics, Industrial Engineering, Operations Research, or related quantitative analytics field AND 1-3 years of experience expected to have analytic maturity, with knowledge of SQL and various statistical modeling or machine learning techniques
OR
Master’s Degree Bachelor’s Degree in Computer Science, Statistics, Physics, Econometrics, Industrial Engineering, Operations Research, or related quantitative analytics field AND experience expected to have analytic maturity, with knowledge of SQL and various statistical modeling or machine learning techniques

Preferred Education / Experience
Very highly preferred to have a Ph.D. in Computer Science, Statistics, Physics, Econometrics, Industrial Engineering, Operations Research, or related quantitative analytics field

Educational level:

Master Degree

Level of experience (years):

Mid Career (2+ years of experience)

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