Senior Data Scientist

Grainger Businesses•Lake Forest, IL

1d•Hybrid

About The Position

W.W. Grainger, Inc., is a leading broad line distributor with operations primarily in North America, Japan and the United Kingdom. At Grainger, We Keep the World Working® by serving more than 4.5 million customers worldwide with products and solutions delivered through innovative technology and deep customer relationships. Known for its commitment to service and award-winning culture, the Company had 2024 revenue of $17.2 billion across its two business models. In the High-Touch Solutions segment, Grainger offers approximately 2 million maintenances, repair and operating (MRO) products and services, including technical support and inventory management. In the Endless Assortment segment, Zoro.com offers customers access to more than 14 million products, and MonotaRO.com offers more than 24 million products. For more information, visit www.grainger.com. W.W. Grainger, Inc. is seeking a Senior Data Scientist in Lake Forest, IL.

Requirements

Bachelor’s degree in Computational Analysis and Public Policy, Statistics, Mathematics, Data Science, Applied Analytics, Operations Research, Applied Science or Engineering, or related field
3 years of related experience
Proficient in usage of databases (e.g. Teradata, Snowflake, Oracle) and querying languages (e.g. SQL)
Knowledge of one or more of the following programming languages: Python, R, SPSS, or SAS
Proficiency with extraction and manipulation of very large structured and unstructured datasets
Proficiency with data visualization techniques
Proficiency with multi-variate linear regression, logistic regression, and time series modeling
Proficiency with statistical design of experiments, outlier detection methods, and statistical hypothesis testing
Proficiency with clustering and dimension reduction techniques
Knowledge of classification, gradient-boosting, and natural language processing algorithms
Experience leveraging cloud-based machine learning resources such as those from AWS
Demonstrated ability to translate analytical work into presentations (e.g. PowerPoint) suitable for non-technical audiences
Demonstrated ability to collaborate with business partners and colleagues

Responsibilities

Design and conduct experiments, quasi-experiments and impact evaluation methodologies to perform causal inferences, statistical analyses and evaluate the performance of various interventions
Conduct exploratory data analysis and apply deep domain knowledge to consumer and sector-specific data to uncover new analytical insights