Grainger is looking to leverage data science to build and maintain large-scale statistical models that turn data points into insights and actions, supporting business decisions and product development.
Requirements
- Proficiency in databases such as Teradata, Snowflake or Oracle and querying languages (e.g. SQL)
- Experienced with at least one data science programming languages (e.g., Python, R, SPSS, or SAS) and working with structured and unstructured datasets
- 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 with data visualization techniques and tools
- Experience translating work into presentations (e.g. PowerPoint) suitable for non-technical audience
Responsibilities
- Propose and evaluate innovative solutions for analyzing, clustering, associating, and classifying data
- Develop and validates algorithms via analysis, computer simulation, and prototyping
- Extend analytics platform for connected devices and sensors
- Write and debugs production code that spans the vertical from database to computational layer to web service
- Helps maintain large-scale analytics infrastructure, including distributed storage and computation clusters
- Deliver insights derived from complex data analysis into simple conclusions that impact leadership to drive action and communicates results to internal and public forums
- contributes to the development of peer-reviewed articles, events and workshops as needed
Other
- This is a hybrid position that is based onsite in Lake Forest or Chicago, IL 3 days a week.
- Work collaboratively with QA team to assist in identifying and developing a wide-range view of individual case studies.
- Work cross-functionally, serves as a knowledge base, and facilitates training to research partners on the development of data science models that will drive critical business decisions
- Participate in brain storming sessions and works collaboratively with engineering and production teams on the development and deployment of products
- Bachelor's degree in Statistics, Mathematics, Computer Science, or other quantitative field
