Data Scientist

Work Location Type:
Hybrid Req Number 324298

About Grainger: 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 maintenance, repair and operating (MRO) products and services, including technical support and inventory management. In the Endless Assortment segment, offers customers access to more than 14 million products, and offers more than 24 million products. For more information, visit

The anticipated base pay compensation range for this position is $85,300.00 to $.

This position is not eligible for any form of sponsorship now or in the future. Individuals requiring sponsorship (e.g. OPT or H1B visa status) should not apply. Only individuals authorized to work in the United States now and for the foreseeable future will be considered for this position.

With benefits starting on day one, our programs provide choice and flexibility to meet team members’ individual needs, including:

• Medical, dental, vision, and life insurance plans with coverage starting on day one of employment and 6 free sessions each year with a licensed therapist to support your emotional wellbeing.
• 18 paid time off (PTO) days annually for full-time employees (accrual prorated based on employment start date) and 6 company holidays per year.
• 6% company contribution to a 401(k) Retirement Savings Plan each pay period, no employee contribution required.
• Employee discounts, tuition reimbursement, student loan refinancing and free access to financial counseling, education, and tools.
• Maternity support programs, nursing benefits, and up to 14 weeks paid leave for birth parents and up to 4 weeks paid leave for non-birth parents.

For additional information and details regarding Grainger’s benefits, please click on the link below:

The pay range provided above is not a guarantee of compensation. The range reflects the potential base pay for this role at the time of this posting based on the job grade for this position. Individual base pay compensation will depend, in part, on factors such as geographic work location and relevant experience and skills. The anticipated compensation range described above is subject to change and the compensation ultimately paid may be higher or lower than the range described above.

Grainger reserves the right to amend, modify, or terminate its compensation and benefit programs in its sole discretion at any time, consistent with applicable law.

The Data Scientist plays a pivotal role in advancing Grainger’s strategic objectives by leveraging machine learning and statistical analysis to uncover insights that drive business value and fuel bottom-line growth. As part of the Finance organization, you will generate high-quality, data-driven insights that inform critical decisions and tell compelling stories behind the numbers. You’ll challenge the status quo, embrace complex problems, think big, and pursue innovative solutions that support Grainger’s mission to keep our customers’ operations running and their people safe.

• Work closely with the business to understand the problem space, identify the opportunities, and translate business problems into technical solutions using machine learning frameworks.
• Conduct exploratory data analysis and apply deep business knowledge to customer and marketplace data to uncover new business insights.
• Manipulate high-volume, high-dimensionality data from multiple sources, visualize patterns, anomalies, relationships, and trends, and perform feature engineering and selection.
• Design and conduct experiments, collect the data necessary to perform statistical hypothesis testing, and create inferences and recommendations.
• Create scalable, efficient,…