Imperial Supplies, a Grainger Company, is seeking a Data Scientist to drive data-driven decision-making across the organization by designing and implementing statistical models and machine learning applications to uncover actionable insights and create measurable business value.
Requirements
- Master’s degree in Data Science, Statistics, Economics, Mathematics, Computer Science, or a related quantitative field — or equivalent work experience.
- At least 1 year of experience in a data science or related analytics role.
- Proficiency in R and/or Python, SQL, Power BI, and machine learning techniques (e.g., clustering, classification, regression).
- Strong skills in data mining, algorithm development, and performance testing.
- 3+ years of experience in a data science role.
- Familiarity with tools such as Snowflake, Smartsheet, or Jira.
- Demonstrated experience using large and multiple datasets to drive business value.
Responsibilities
- Collect, organize, and analyze large datasets from internal and external sources to support predictive modeling and strategic recommendations.
- Develop, test, and validate custom models, algorithms, and simulations using R/Python and SQL.
- Research and build machine learning applications involving structured and unstructured data, including regression, classification, and clustering models.
- Create automated processes to test and monitor model performance and ensure data accuracy.
- Develop and own measurement plans in partnership with key stakeholders.
- Build dynamic data visualizations using Power BI to monitor key business trends and metrics.
- Stay current on advancements in data science methodologies and tools, fostering innovation in analytical processes.
Other
- Excellent communication and presentation skills, with the ability to translate complex data into actionable insights.
- Strong organization and time management skills with the ability to manage multiple priorities in a fast-paced environment.
- Proven ability to work cross-functionally with stakeholders at all levels.
- Hybrid / Remote schedule.
- Work/Life balance.
