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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Scientist - **Company:** GRAINGER, INC. - **Location:** Chicago, IL, United States - **Experience:** Expert - **Salary:** $103,600.0 - $172,600.0 - **Contract:** Permanent contract - **Skills:** Amazon Web Services, Data Analysis, Databases, Data Visualization, Statistical Hypothesis Testing, Python (Programming Language), Linear Regression, Logistic Regression, Machine Learning, Natural Language Processing, Oracle (Applications), Microsoft PowerPoint, SQL Databases, Teradata SQL, Unstructured Data, Feature Engineering, Snowflake, Model Validation, Build Tools, Streamlit Framework - **Published:** August 5, 2026 - **Apply:** https://jobs.localjobnetwork.com/apply/add/87971381/1 ## About the Role We are looking for a Data Scientist to join our Digital Experience Analytics team who is passionate about using data and advanced quantitative methods to provide tangible, long-term monetary benefits to our organization. We're looking for people who never stop learning. Having a desire to learn new skills and seek out new information about our business, our customers, and our work is important to maintain our success for the next 90 years. The Sr. Data Scientist will support the Digital organization by: 1) supporting digital experimentation 2) Developing and deploying statistical and machine learning models that improve the effectiveness of our digital operations 3) Measuring and identifying the drivers of digital performance, * Bachelor's Degree BS in technical field such as Statistics, Mathematics, Data Science, Applied Analytics, Operations Research, Applied Science or Engineering required -or- Bachelor in a Social Science with exposure to quantitative methods such as Economics, Political Science, Psychology or Sociology. * Master's or Ph.D. in a Quantitative field such as Statistics, Mathematics, Data Science, Applied Analytics or in a Social Science with a quantitative focus such as Economics, Political Science, Psychology or Sociology. * 3+ years' experience in analytics and data science roles required * Exposure to the statistical design of experiments and statistical hypothesis testing * 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. * 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 * 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 Preferred * Familiarity with basic statistical concepts related to experimentation and causal inference such as randomization * Experience with Python or R-based dashboarding tools such as Streamlit, Dash or Shiny * The ability to collaborate with non-technical stakeholders and communicate complex technical topics to a non-technical audience. ## Description * Build tools to automate and standardize experiments on Grainger's e-commerce platform * Become and serve as a subject-matter expert for one of Grainger's digital products (e.g. search, recommendations, checkout, etc.) * Analyze data sets, build predictive models, deploy and operationalize solutions to enhance organizational performance. * Apply techniques such as classification, clustering, dimension reduction, regression, NLP, time series forecasting, and boosting to build explanatory, predictive, and prescriptive pricing models appropriate for solving different business problems. * Conduct exploratory data analysis and apply deep business knowledge to customers and marketplace data to uncover new insights. * Create and present the materials necessary to communicate the results of analytical work and associated recommendations and influence the use of analytical recommendations. * Manipulate high-volume, high-dimensionality data from multiple sources, visualize patterns, anomalies, relationships, and trends, and perform feature engineering and selection. * Create the code to support large-scale data analyses, model development, model validation and deployment. * Assist junior team members in developing new skills and knowledge. ## Related Videos - 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