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Grainger

Data Scientist

Reposted 3 Hours Ago
Hybrid
Lake Forest, IL
87K-145K Annually
Junior
Hybrid
Lake Forest, IL
87K-145K Annually
Junior
Perform exploratory analysis, feature engineering, and build ML/statistical models (classification, regression, clustering, NLP, deep learning, time series) to generate data-driven insights for Finance. Design experiments, validate and deploy scalable pipelines, visualize results, and present recommendations to non-technical stakeholders while partnering with business teams and developing domain expertise in MRO.
The summary above was generated by AI
Work Location Type: Hybrid
Req Number 332907
About Grainger
W.W. Grainger, Inc. is a leading broad line distributor with operations primarily in North America and Japan. At Grainger, We Keep the World Working® by serving more than 4.6 million customers worldwide with maintenance, repair and operating (MRO) products and value-added solutions delivered through innovative technology and deep customer expertise. Known for its commitment to service and purpose-driven culture, the Company reported 2025 revenue of $17.9 billion. For more information, visit www.grainger.com.
Compensation
The anticipated base pay compensation range for this position is $87,200.00 - $145,300.00. This role is eligible for an incentive target of up to 5 % or $ , based on the achievement of individual and company performance objectives in accordance with the current terms of the incentive program which are subject to change.
Rewards and Benefits
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:
https://experience100.ehr.com/grainger/Home/Tools-Resources/Key-Resources/New-Hire
Grainger Benefits
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.
Position Details:
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.
You Will:
  • 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 customers 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, automated processes to support large scale data analyses, model development, model validation and deployment. Apply techniques such as classification, clustering, dimension reduction, regression, NLP, deep learning, time series forecasting to build explanatory, predictive, prescriptive models appropriate for solving different business problems.
  • 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.

You Have :
  • Bachelor's Degree in Data Science, Statistics, Mathematics, Computer Science, or other quantitative field and/or Master's Degree Data Science, Statistics, Mathematics, Computer Science, or other quantitative field.
  • Minimum 2+ years' experience in Data science or statistics-related work experience
  • Proficiency in databases such as Snowflake, Teradata, or Oracle and querying languages (e.g. SQL).
  • Experienced with at least one data science programming languages (e.g., Python, R) and working with structured and unstructured datasets.
  • Experience with machine learning techniques such as classification, clustering, dimension reduction, regression, NLP algorithms, and time series modeling.
  • Experience with statistical design of experiments, outlier detection methods, and statistical hypothesis testing.
  • Experience with data visualization techniques and tools.
  • Experience translating work into presentations (e.g. PowerPoint) suitable for non-technical audience.
  • Demonstrated ability to collaborate with business partners and colleagues.

We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex (including pregnancy), national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or expression, protected veteran status or any other protected characteristic under federal, state, or local law. We are proud to be an equal opportunity workplace.
We are committed to fostering an inclusive, accessible work environment that includes both providing reasonable accommodations to individuals with disabilities during the application and hiring process as well as throughout the course of one's employment, should you need a reasonable accommodation during the application and selection process, including, but not limited to use of our website, any part of the application, interview or hiring process, please advise us so that we can provide appropriate assistance.

Grainger Chicago, Illinois, USA Office

In the heart of Chicago's River North neighborhood, Grainger's offices at theMART are walking distance from many transit stations and moments from the expressway. This prime location and open floor offices help team members collaborate and build the best solutions as they bring new ideas to life.

Product

At Grainger, team members are always experimenting and discovering new ways to use technology to connect maintenance, repair and operations (MRO) customers to the products they need to keep their business up and running and their people safe. “Working on the Grainger Product team means I get to solve mission critical issues that move the entire business forward,” says Dahlia Block, Software Engineer, Product and Platform Engineering. Ryan Chamberlin, Manager of Product Engineering agrees, “Grainger is committed to continuous improvement and innovation, which creates exciting opportunities for employees to learn and grow.”

AI & Machine Learning

We are designing, delivering, and operating the digital experiences, tools, and information assets that solve customers’ problems. Our scale presents complex and interesting engineering challenges that are solved by technologists at the top of their game. Alan Cooney, Senior Manager of Applied Machine Learning shares, “Over the past few years, we have integrated ML into many aspects of our customer interactions- all with a focus of making the experience better for our customer’s." David Brenner, Director of Product Management shared similar sentiments, stating, “Grainger’s purpose: We Keep The World Working® is apparent in the way we design, deliver, and operate digital experiences, tools, and information that solve customers’ needs."

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