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Data Scientist

Date: Nov 27, 2021

Location: LAKE FOREST, IL, US, 60045-5201 CHICAGO, IL, US, 60603-4013

Company: Grainger Businesses


Grainger is North America's leading distributor of maintenance, repair, and operating products and services. Our wide assortment, deep expertise, innovative technology solutions and unparalleled customer service keep customers' operations running and their people safe.

We're looking for passionate people who can move our company forward. We have a welcoming workplace where you can build a career for yourself while fulfilling our purpose to keep the world working. We embrace new ways of thinking and recognize everyone is an individual. Find your way at Grainger.

At Grainger, using insights to better serve our customers has been foundtional to our company’s success. It started with Bill Grainger identifying the need for a consistent supply of Motors to serve America’s rapidly mechanizing economy over 90 years ago.  And even though a lot has changed since then, generating new insights remains critical to our business. Except now we harness massive amounts of data, cutting edge technology, advanced analytical techniques, and the best people in the industry to inform decisions across the company. 


We are looking for exceptional data scientists to join 50+ other Analytics and Data team members in our center of excellence supporting the entire business - who are passionate about leveraging data and advanced quantitative methods to provide tangible, long-term monetary benefits to the organization. We're looking for people who never stop learning.  Having a strong desire to learn new skills and proactively seek out new information about our business, our customers, and our work is critical to maintaining our companies future success.

The Data Scientist will solve complex, data intensive problems by

  1. Creating perspectives on customers and marketplace dynamics that inform strategic choices
  2. Developing and deploying statistical and machine learning models that improve the effectiveness of our business operations
  3. Measuring and identifying the drivers of business performance


  • Work closely with the business to understand the problem space, identify the opportunities, and translate business problems into analytical solutions
  • Apply techniques such as classification, clustering, dimension reduction, regression, NLP, time series forecasting, and boosting to build explanatory, predictive, and prescriptive models appropriate for solving different business problems
  • Design and conduct experiments, collect the data necessary to perform statistical hypothesis testing, and create inferences and recommendations
  • Conduct exploratory data analysis and apply deep business knowledge to customer and marketplace data to uncover new business insights
  • Create and present the materials necessary to effectively communicate the results of analytical work and associated recommendations
  • Develop expertise on Grainger’s business operations, go-to-market model, and the broader Maintenance, Repair, and Operations (MRO) market 
  • Manipulate high-volume, high-dimensionality data from multiple sources, visualize patterns, anomalies, relationships, and trends, and perform feature engineering and selection
  • Create and maintain the code to support large scale data analyses, model development, model validation and deployment


  • 2+ years of experience in analytics and data science roles or advanced degree
  • BS, MS, or PhD in a technical field such as Statistics, Mathematics, Data Science, Applied Analytics, Operations Research, Applied Science or Engineering
  • Strong business acumen
  • Excellent communication skills
  • Proficient with usage of databases (e.g. Teradata, Snowflake, Oracle) and querying languages (e.g. SQL)
  • Highly skilled with one or more of the following programming languages: Python, R, SPSS, or SAS
  • Experience working with very large structured and unstructured datasets
  • Experience with data visualization techniques
  • Experience with multi-variate linear regression, logistic regression, and time series modeling
  • Experience with statistical design of experiments, outlier detection methods, and statistical hypothesis testing
  • Experience translating analytical work into presentations (e.g. PowerPoint) suitable for non-technical audiences
  • Demonstrated ability to collaborate with business partners and colleagues
  • MS or higher preferred
  • Experience with clustering and dimension reduction techniques
  • Experience with classification, gradient-boosting, and natural language processing algorithms
  • Expereince leveraging cloud-based machine learning resources such as those from AWS


We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, or veteran status. We are proud to be an equal opportunity workplace.