Job description

Data Scientist

At Grainger, using insights to better serve our customers has been foundational 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 our Pricing Data Science team 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 maintain our company’s success for the next 90 years.

The Data Scientist assist in the pricing process by:

  • Creating perspectives on customers and product dynamics that inform strategic pricing decisions
  • Developing and deploying statistical and machine learning models that improve the effectiveness of our pricing operations
  • Measuring and identifying the drivers of pricing performance

Core responsibilities:

  • Work closely with the pricing team to understand the problem space, identify the opportunities, and translate pricing questions into analytical solutions
  • Apply techniques such as classification, clustering, dimension reduction, regression, NLP, time series forecasting, and boosting to build explanatory, predictive, and prescriptive pricing models
  • Design and conduct pricing experiments, collect the data necessary to perform statistical hypothesis testing, and create inferences and recommendations
  • Conduct exploratory data analysis and apply deep business/pricing knowledge to customer and product data to uncover new pricing 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

Required Education/Experience:

  • 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

Preferred Education/Experience:

  • MS or higher preferred
  • Experience in Pricing Analytics or Data Science
  • Experience with clustering and dimension reduction techniques
  • Experience with classification, gradient-boosting, and natural language processing algorithms

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